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Question #3457 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Currently stored (rendered) A triangle with angle measures 30°, 60°, and 90° has a perimeter of 18 + 6 × 3 18 + 6 \times \sqrt{3} 18 + 6 × 3 . What is the length of the longest side of the triangle?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "2 to 1 to the square root of 3": leftover tokens: [{"t":"word","v":"to","raw":"to"},{"t":"num","v":"1"},{"t":"word","v":"to","raw":"to"},{"t":"word","v":"the","raw":"the"},{"t":"word","v":"square","raw":"square"},{"t":"word","v":"root","raw":"root"},{"t":"word","v":"of","raw":"of"},{"t":"num","v":"3"}]
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Question #3452 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Currently stored (rendered)
In the figure above,
B D = 6 BD = 6 B D = 6 and
A D = 8 AD = 8 A D = 8 . What is the length of
D C ‾ \overline{DC} D C ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
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" alt="The figure presents right triangle A B C . Side A C is horizontal, vertex C is to the right of vertex A, vertex B is above side A C , and angle A B C is a right angle. Point D lies on side A C, directly below vertex B, and vertical line segment B D is drawn, dividing triangle A B C into two smaller triangles, triangle A B D and triangle B D C. Angle A D B is a right angle. A note states that the figure is not drawn to scale." /></div>
</div>
<p class="stem_paragraph ">In the figure above, <span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mi>D</mi><mo>=</mo><mn>6</mn></mrow><annotation encoding="application/x-tex">BD = 6</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">6</span></span></span></span></span></span> and <span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mi>D</mi><mo>=</mo><mn>8</mn></mrow><annotation encoding="application/x-tex">AD = 8</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">8</span></span></span></span></span></span>. What is the length of <span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>D</mi><mi>C</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{DC}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3443 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Currently stored (rendered)
In the figure above, B D ‾ \overline{BD} B D is parallel to A E ‾ \overline{AE} A E . What is the length of C E ‾ \overline{CE} C E ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "the length of side C E equal to 30": leftover tokens: [{"t":"word","v":"equal","raw":"equal"},{"t":"word","v":"to","raw":"to"},{"t":"num","v":"30"}]
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" alt="The figure presents triangle A, C E, with horizontal side A, C. Side A, E, is perpendicular to side A, C, such that point E, is above point A. Point B, lies on horizontal side A, C, point D, lies on hypotenuse C E, and line segment B D, is drawn such that it is parallel to side A, E, and forms triangle C D B. Side A, E, is labeled 18, side B C, is labeled 8, side B D, is labeled 6, and a right angle symbol is at point A" /></div>
</div>
</div>
<p class="stem_paragraph ">In the figure above, <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>B</mi><mi>D</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{BD}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span> is parallel to <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>A</mi><mi>E</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{AE}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span><span class="math_expression "></span>. What is the length of <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>C</mi><mi>E</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{CE}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0715em;">C</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3440 · Question bank · math · Geometry and Trigonometry · type: mcqno answer key
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Question #3435 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3429 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3424 · Question bank · math · Geometry and Trigonometry · type: mcq
Currently stored (rendered) The volume of right circular cylinder A is 22 cubic centimeters. What is the volume, in cubic centimeters, of a right circular cylinder with twice the radius and half the height of cylinder A?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "4 pi r squared, times, one half h, and equals 2 pi r squared times h": unexpected token: {"t":"word","v":"equals","raw":"equals"}
Corrected stem text <p class="stem_paragraph ">The volume of right circular cylinder A is 22 cubic centimeters. What is the volume, in cubic centimeters, of a right circular cylinder with twice the radius and half the height of cylinder A?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3421 · Question bank · math · Geometry and Trigonometry · type: mcq
Currently stored (rendered)
In the x y xy x y -plane above, points P P P , Q Q Q , R R R , and T T T lie on the circle with center O O O . The degree measures of angles P O Q P O Q P O Q and R O T R O T R O T are each 30°. What is the radian measure of angle Q O R Q O R QO R ?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "the fraction 360 degrees over 2 pi radians, equals, the fraction 120 degrees over x radians": leftover tokens: [{"t":"word","v":"radians","raw":"radians"},{"t":"comma","v":","},{"t":"word","v":"equals","raw":"equals"},{"t":"comma","v":","},{"t":"word","v":"the","raw":"the"},{"t":"word","v":"fraction","raw":"fraction"},{"t":"num","v":"120"},{"t":"word","v":"degrees","raw":"degrees"},{"t":"word","v":"over","raw":"over"},{"t":"word","v":"x","raw":"x"},{"t":"word","v":"radians","raw":"radians"}]
Corrected stem text <div class="stimulus_reference ">
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" alt="The figure presents a circle in the x y plane, with the origin labeled O. The center of the circle lies at the origin. There are 4 points, T, R, Q, and P, labeled clockwise on the circle. Point T lies on the x axis, directly to the left of the origin, and has coordinates negative 1 comma 0. Point R lies above the x axis, and to the left of the y axis. Point Q lies above the x axis and to the right of the y axis. Point P lies on the x axis, directly to the right of the origin, and has coordinates 1 comma 0. Points R and Q appear to be symmetric with respect to the y axis. Four line segments are drawn from the origin to each of the four points on the circle." /></div>
</div>
<p class="stem_paragraph ">In the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane above, points <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi></mrow><annotation encoding="application/x-tex">P</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>Q</mi></mrow><annotation encoding="application/x-tex">Q</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">Q</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi></mrow><annotation encoding="application/x-tex">R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>T</mi></mrow><annotation encoding="application/x-tex">T</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span></span></span></span> lie on the circle with center <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>O</mi></mrow><annotation encoding="application/x-tex">O</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">O</span></span></span></span>. The degree measures of angles <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi><mi>O</mi><mi>Q</mi></mrow><annotation encoding="application/x-tex">P O Q</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mord mathnormal" style="margin-right:0.0278em;">O</span><span class="mord mathnormal">Q</span></span></span></span></span></span> and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi><mi>O</mi><mi>T</mi></mrow><annotation encoding="application/x-tex">R O T</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span><span class="mord mathnormal" style="margin-right:0.0278em;">O</span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span></span></span></span></span></span> are each 30°. What is the <u><span class="underline ">radian</span></u> measure of angle <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>Q</mi><mi>O</mi><mi>R</mi></mrow><annotation encoding="application/x-tex">Q O R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">QO</span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3414 · Question bank · math · Geometry and Trigonometry · type: mcq
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In above, what is the length of ?
Flag reason: 2 math-img alt-text failed MathSpeak conversion: "triangle A, B C": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "segment A, D": unexpected token: {"t":"word","v":"segment","raw":"segment"}
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" alt="The figure presents triangle A, B C, where side A, C is horizontal and point B is above side A, C. Point D lies on side A, C, and line segment B D is drawn, forming right angle B D C. Side B C is labeled 12. Angle A, B D is labeled 30 degrees and angle B C D is labeled 60 degrees." /></div>
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<p class="stem_paragraph ">In <span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="triangle A, B C" /></span> above, what is the length of <span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABkAAAAeCAYAAADZ7LXbAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAABGJhU0UAAAAPUJuPDwAAAAFzUkdCAK7OHOkAAAAEZ0FNQQAAsY8L/GEFAAAA1ElEQVRIS+1U2w3EIAxjPAbKOOzCKmziC49SUJ305073g6WoaoMTx6kIA/hxHHwBKAmx+RmRCqivyLL6PiMqQZ/vyKIEEYiSJPMm7UwQaHrmoW+V89qoK6wT2ASgIMUqJD9zjb8337CS3ULDTi6gi7McWKboB7ptllq+L9cyprykiBCTZvZirTn5XuE3IeqYv56NFaZdFpE2Hvt4FBlgwhqaLZq3Yi3o7aOC7vEajy6Y+Ovuw5/C+lN2G11B1oTz+iCkC6vy+7oh4dQ4ODg4OPgPQvgALcVwbJFs9QwAAAAASUVORK5CYII=" alt="segment A, D" /></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3402 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Triangle A B C ABC A B C and triangle D E F DEF D E F are shown. The relationship between the side lengths of the two triangles is such that A B D E = B C E F = A C D F = 3 \dfrac{AB}{DE} = \dfrac{BC}{EF} = \dfrac{AC}{DF} = 3 D E A B = E F B C = D F A C = 3 . If the measure of angle B A C BAC B A C is 20°, what is the measure, in degrees, of angle E D F EDF E D F ? (Disregard the degree symbol when gridding your answer.)
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" alt="The figure presents two triangles, triangle A, B C and triangle D E F. The two triangles are placed side by side, and triangle A, B C is larger than triangle D E F. In triangle A, B C, side A, B slants upward and to the right, side B C slants downward and to the right, and side A, C slants slightly upward and to the right. In triangle D E F, side D E slants upward and to the right, side E F slants downward and to the right, and side D F slants slightly upward and to the right. A note indicates that the figures are not drawn to scale." /></div>
</div>
<p class="stem_paragraph ">Triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mi>B</mi><mi>C</mi></mrow><annotation encoding="application/x-tex">ABC</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span> and triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>D</mi><mi>E</mi><mi>F</mi></mrow><annotation encoding="application/x-tex">DEF</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span> are shown. The relationship between the side lengths of the two triangles is such that <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mi>A</mi><mi>B</mi></mrow><mrow><mi>D</mi><mi>E</mi></mrow></mfrac></mstyle><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mi>B</mi><mi>C</mi></mrow><mrow><mi>E</mi><mi>F</mi></mrow></mfrac></mstyle><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mi>A</mi><mi>C</mi></mrow><mrow><mi>D</mi><mi>F</mi></mrow></mfrac></mstyle><mo>=</mo><mn>3</mn></mrow><annotation encoding="application/x-tex">\dfrac{AB}{DE} = \dfrac{BC}{EF} = \dfrac{AC}{DF} = 3</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:2.0463em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3603em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0463em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3603em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0463em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3603em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">3</span></span></span></span></span></span>. If the measure of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mi>A</mi><mi>C</mi></mrow><annotation encoding="application/x-tex">BAC</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span> is 20°, what is the measure, in degrees, of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>E</mi><mi>D</mi><mi>F</mi></mrow><annotation encoding="application/x-tex">EDF</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span> ? (Disregard the degree symbol when gridding your answer.)</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #3394 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3382 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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The area of triangle A B C ABC A B C above is at least 48 but no more than 60. If y y y is an integer, what is one possible value of x x x ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "y equals 8, 9, or 10": leftover tokens: [{"t":"word","v":"or","raw":"or"},{"t":"num","v":"10"}]
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" alt="The figure presents right triangle A B C, where angle C is a right angle. Side A C is horizontal, such that vertex A is to the left of vertex C, and vertex B is directly above vertex C. A vertical line segment is drawn from a point on side A B to a point on side A C and divides side A C into two segments. The length of the segment between vertex A and the vertical line segment is labeled 5 and the length of the segment between the vertical line segment and vertex C is labeled 7. The vertical line segment is labeled x. Side B C is labeled y. A note states the figure is not drawn to scale." /></div>
</div>
<p class="stem_paragraph ">The area of triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mi>B</mi><mi>C</mi></mrow><annotation encoding="application/x-tex">ABC</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span> above is at least 48 but <span class="formatted_line_break delivery_mode:Both "></span>no more than 60. If <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span> is an integer, what is one <span class="formatted_line_break delivery_mode:Both "></span>possible value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3379 · Question bank · math · Geometry and Trigonometry · type: mcq
Source PDF page (reference) No source page on record.
Question #3374 · Question bank · math · Geometry and Trigonometry · type: mcq
Currently stored (rendered)
In the figure above, R T = T U R T = T U R T = T U . What is the value of x x x ?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "triangle R T U": unexpected token: {"t":"word","v":"triangle","raw":"triangle"}
Corrected stem text <div class="stimulus_reference ">
<div class="standalone_image "><img 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" alt="The figure presents triangle R T U, with R U horizontal, and U to the right of R. A point V is on R U, such that V is closer to R than it is to U. Vertex T is above R U. The angle at T is labeled 114 degrees. Side U T is extended to point S, above vertex R, and line segment S V is drawn. The angle to the right of S V and below S T is labeled 31 degrees. The angle to the left of S V and above R V is labeled x degrees." /></div>
</div>
<p class="stem_paragraph ">In the figure above, <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi><mi>T</mi><mo>=</mo><mi>T</mi><mi>U</mi></mrow><annotation encoding="application/x-tex">R T = T U</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span><span class="mord mathnormal" style="margin-right:0.109em;">U</span></span></span></span></span></span>. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3370 · Question bank · math · Geometry and Trigonometry · type: mcqno answer key
Currently stored (rendered) At a certain time and day, the Washington Monument in Washington, DC, casts a shadow that is 300 feet long. At the same time, a nearby cherry tree casts a shadow that is 16 feet long. Given that the Washington Monument is approximately 555 feet tall, which of the following is closest to the height, in feet, of the cherry tree?
Flag reason: no correct_choice in source data
Corrected stem text <p class="stem_paragraph ">At a certain time and day, the Washington Monument in Washington, DC, casts a shadow that is 300 feet long. At the same time, a nearby cherry tree casts a shadow that is 16 feet long. Given that the Washington Monument is approximately 555 feet tall, which of the following is closest to the height, in feet, of the cherry tree?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3369 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Source PDF page (reference) No source page on record.
Question #3367 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Currently stored (rendered)
In the figure above, tan ( B ) = 3 4 \tan\left(B\right) = \dfrac{3}{4} tan ( B ) = 4 3 . If B C = 15 B C = 15 B C = 15 and D A = 4 D A = 4 D A = 4 , what is the length of D E ‾ \overline{DE} D E ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 4 math-img alt-text failed MathSpeak conversion: "triangle A, B C": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "triangle D B E": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "triangle A, B C ": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "triangle D B E": unexpected token: {"t":"word","v":"triangle","raw":"triangle"}
Corrected stem text <div class="stimulus_reference ">
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<img 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" alt="The figure presents right triangle A, B C, with horizontal side A, C. Point B is directly above point A and angle A is a right angle. Point D lies on side A, B and point E lies on side B C. Horizontal line segment D E is drawn and angle D is a right angle." /></div>
</div>
<p class="stem_paragraph ">In the figure above, <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>tan</mi><mo></mo><mrow><mo fence="true">(</mo><mi>B</mi><mo fence="true">)</mo></mrow><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>3</mn><mn>4</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\tan\left(B\right) = \dfrac{3}{4}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mop">tan</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">4</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">3</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span><span class="math_expression "></span>. If <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi><mi>C</mi><mo>=</mo><mn>15</mn></mrow><annotation encoding="application/x-tex">B C = 15</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">15</span></span></span></span></span></span> and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>D</mi><mi>A</mi><mo>=</mo><mn>4</mn></mrow><annotation encoding="application/x-tex">D A = 4</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal">A</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">4</span></span></span></span></span></span>, what is the length of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>D</mi><mi>E</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{DE}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3360 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3355 · Question bank · math · Geometry and Trigonometry · type: mcq
Currently stored (rendered)
In the figure above, what is the length of N Q ‾ \overline{NQ} N Q ?
Flag reason: 3 math-img alt-text failed MathSpeak conversion: "triangle M N P": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "triangle M N P": unexpected token: {"t":"word","v":"triangle","raw":"triangle"} | "triangle N Q P": unexpected token: {"t":"word","v":"triangle","raw":"triangle"}
Corrected stem text <div class="stimulus_reference ">
<div class="standalone_image "><img 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" alt="The figure presents right triangle M N P. Side M P is horizontal, with vertex M to the left of vertex P. Vertex N lies above side M P, and angle N is a right angle. Point Q lies on horizontal side M P directly below vertex N. Vertical line segment N Q is drawn, forming right triangles M N Q and Q N P. Side M N is labeled 3 and side N P is labeled 4." /></div>
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<p class="stem_paragraph ">In the figure above, what is the length of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>N</mi><mi>Q</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{NQ}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.0778em;vertical-align:-0.1944em;"></span><span class="mord overline"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.109em;">N</span><span class="mord mathnormal">Q</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1944em;"><span></span></span></span></span></span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3335 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3326 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Question #3318 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Currently stored (rendered)
In the figure above, M Q ‾ \overline{MQ} M Q and N R ‾ \overline{NR} N R intersect at point P P P , N P = Q P N P = Q P N P = QP , and M P = P R M P = P R M P = P R . What is the measure, in degrees, of ∠ Q M R \angle QMR ∠ QM R ? (Disregard the degree symbol when gridding your answer.)
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" alt="The figure presents line segments MQ and NR that intersect at point P, where point N is above and slightly to the right of point M and point Q is above and slightly to the left of point R. Line segments MN, QR, and horizontal line segment M, R are drawn forming triangles MNR and QMR. The measure of angle QPR is labeled 60 degrees and the angle measure of MQR is labeled 70 degrees." /></div>
</div>
<p class="stem_paragraph ">In the figure above, <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>M</mi><mi>Q</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{MQ}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.0778em;vertical-align:-0.1944em;"></span><span class="mord overline"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.109em;">M</span><span class="mord mathnormal">Q</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1944em;"><span></span></span></span></span></span></span></span></span></span></span> and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mover accent="true"><mrow><mi>N</mi><mi>R</mi></mrow><mo stretchy="true">‾</mo></mover></mrow><annotation encoding="application/x-tex">\overline{NR}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8833em;"></span><span class="mord overline"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8833em;"><span style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.109em;">N</span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span><span style="top:-3.8033em;"><span class="pstrut" style="height:3em;"></span><span class="overline-line" style="border-bottom-width:0.04em;"></span></span></span></span></span></span></span></span></span></span></span> intersect at point <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi></mrow><annotation encoding="application/x-tex">P</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span></span></span></span>, <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>N</mi><mi>P</mi><mo>=</mo><mi>Q</mi><mi>P</mi></mrow><annotation encoding="application/x-tex">N P = Q P</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.109em;">N</span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">QP</span></span></span></span></span></span>, and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>M</mi><mi>P</mi><mo>=</mo><mi>P</mi><mi>R</mi></mrow><annotation encoding="application/x-tex">M P = P R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.109em;">M</span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span></span></span>. What is the measure, in degrees, of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">∠</mi><mi>Q</mi><mi>M</mi><mi>R</mi></mrow><annotation encoding="application/x-tex">\angle QMR</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8867em;vertical-align:-0.1944em;"></span><span class="mord">∠</span><span class="mord mathnormal" style="margin-right:0.109em;">QM</span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span></span></span> ? (Disregard the degree symbol when gridding your answer.)</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3310 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
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Intersecting lines r r r , s s s , and t t t are shown below.
What is the value of x x x ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
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<p class="passage_para ">Intersecting lines <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi></mrow><annotation encoding="application/x-tex">r</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>s</mi></mrow><annotation encoding="application/x-tex">s</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">s</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> are shown below.</p>
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<div class="standalone_image "><img 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" alt="The figure presents three intersecting lines, labeled r, s, and t. Line s begins near the top of the figure and extends downward and slightly to the left. Line t begins to the left of line s, and extends downward and to the right, intersecting line s. Line r begins below line t and to the left of line s. Line r extends upward and to the right, first intersecting line s and then line t. The following angle measures are indicated: the angle formed to the right of line s and above line t measures 106 degrees, and the angle formed to the left of line s and above line r measures x degrees. The angle formed below line t and above line r measures 23 degrees." /></div>
</div>
<p class="stem_paragraph ">What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3294 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3285 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3282 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
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Question #3271 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3267 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
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Question #3262 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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The mean of the list of numbers above is what fraction of the sum of the five numbers?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "A list consists of 5 numbers: 2, 10, 3, 7, 6": leftover tokens: [{"t":"word","v":"list","raw":"list"},{"t":"word","v":"consists","raw":"consists"},{"t":"word","v":"of","raw":"of"},{"t":"num","v":"5"},{"t":"word","v":"numbers","raw":"numbers"},{"t":"colon","v":":"},{"t":"num","v":"2"},{"t":"comma","v":","},{"t":"num","v":"10"},{"t":"comma","v":","},{"t":"num","v":"3"},{"t":"comma","v":","},{"t":"num","v":"7"},{"t":"comma","v":","},{"t":"num","v":"6"}]
Corrected stem text <div class="stimulus_reference "><p class="standalone_statement style:1 "><span class="math_expression "><span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="A list consists of 5 numbers: 2, 10, 3, 7, 6" /></span></span></p></div>
<p class="stem_paragraph ">The mean of the list of numbers above is what fraction of the sum of the five numbers?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3260 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
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Question #3241 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered)
Each dot in the scatterplot above represents the temperature and the number of people who visited a beach in Lagos, Nigeria, on one of eleven different days. The line of best fit for the data is also shown. According to the line of best fit, what is the number of people, rounded to the nearest 10, predicted to visit this beach on a day with an average temperature of 32°C?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p><img 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" alt="The figure presents a scatterplot titled “Number of Beach Visitors versus Temperature.” The horizontal axis is labeled “Average temperature, in degrees Celsius,” and the numbers 25 through 35, in increments of 2, are indicated. The vertical axis is labeled “Number of people,” and the numbers 0 through 640, in increments of 80, are indicated. There are 11 data points in the scatterplot that begin near the bottom left portion of the coordinate plane and trend upward and to the right. The line of best fit for the data is also shown. The line of best fit passes through the points with coordinates 25 comma 80 and 32 comma 480." /></p><p class="stem_paragraph ">Each dot in the scatterplot above represents the temperature and the number of people who visited a beach in Lagos, Nigeria, on one of eleven different days. The line of best fit for the data is also shown. According to the line of best fit, what is the number of people, rounded to the nearest 10, predicted to visit this beach on a day with an average temperature of 32°C?</p><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3227 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
The table below shows the distribution of US states according to whether they have a state-level sales tax and a state-level income tax.
2013 State-Level Taxes
State sales tax
No state sales tax
State income tax
39
4
No state income tax
6
1
To the nearest tenth of a percent, what percent of states with a state-level sales tax do not have a state-level income tax?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "6 over 45, equals 0 point 1 3 3 3 dot dot dot": leftover tokens: [{"t":"word","v":"dot","raw":"dot"},{"t":"word","v":"dot","raw":"dot"},{"t":"word","v":"dot","raw":"dot"}]
Corrected stem text <div class="stimulus_reference ">
<div class="passage ">
<div class="prose style:1 ">
<p class="passage_para ">The table below shows the distribution of US states according to whether they have a state-level sales tax and a state-level income tax.</p>
<table class="table_WithBorder">2013 State-Level Taxes
<tbody><tr><td class="tcp-153694c7-8fa3-4e23-94a4-6ea6e2e697de"> </td>
<td class="tcp-e5a53952-9288-40e0-ac19-cafecda65b9b">State sales tax</td>
<td class="tcp-10ebc204-0eda-4bce-ba75-826a9b8a2a82">No state sales tax</td>
</tr><tr><td class="tcp-90f074ad-6769-4a50-ae37-618ca7ff7b31">State income tax</td>
<td class="tcp-97ba8e95-d3bf-4293-b928-e12feb1f5419">39</td>
<td class="tcp-1b3bda3e-5a56-499a-a798-bbd993270702">4</td>
</tr><tr><td class="tcp-c1409411-06b0-4363-89b8-171abff0b8c0">No state income tax</td>
<td class="tcp-43b1ecd9-27b9-4264-9eac-617d6bce776a">6</td>
<td class="tcp-6256a8c4-7f90-4037-ae03-64c4afd368b8">1</td>
</tr></tbody></table><p class="passage_para "> </p>
</div>
</div>
</div>
<p class="stem_paragraph ">To the nearest tenth of a percent, what percent of states with a state-level sales tax do not have a state-level income tax?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3217 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered) If a a a is the mean and b b b is the median of nine consecutive integers, what is the value of ∣ a − b ∣ \left|a - b\right| ∣ a − b ∣ ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "the fraction with numerator open parenthesis, k plus, k plus 1, plus, k plus 2, plus, dot dot dot, plus, k plus 8, close parenthesis, and denominator 9, equals, the fraction with numerator, open parenthesis, 9 k plus 36, close parenthesis, and denominator 9": unexpected token: {"t":"word","v":"dot","raw":"dot"}
Corrected stem text <p class="stem_paragraph ">If <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> is the mean and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> is the median of nine consecutive integers, what is the value of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">∣</mo><mi>a</mi><mo>−</mo><mi>b</mi><mo fence="true">∣</mo></mrow><annotation encoding="application/x-tex">\left|a - b\right|</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">∣</span><span class="mord mathnormal">a</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord mathnormal">b</span><span class="mclose delimcenter" style="top:0em;">∣</span></span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3204 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
Which of the following statements about the means and medians of data set A and data set B is true?
(A) Only the means are different.
(B) Only the medians are different.
(C) Both the means and the medians are different.
(D) Neither the means nor the medians are different.
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "Data set A consists of 9 data values, each of which is the integer 5.
Data set B consists of 10 data values, nine of which are the integer 5, and one of which is the integer 100.": unexpected token: {"t":"word","v":"data","raw":"Data"}
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="Data set A consists of 9 data values, each of which is the integer 5.
Data set B consists of 10 data values, nine of which are the integer 5, and one of which is the integer 100." /></span></p>
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<p class="stem_paragraph ">Which of the following statements about the means and medians of data set A and data set B is true?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3203 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Each dot in the scatterplot above represents the temperature and the number of people who visited a beach in Lagos, Nigeria, on one of eleven different days. The line of best fit for the data is also shown. The line of best fit for the data has a slope of approximately 57. According to this estimate, how many additional people per day are predicted to visit the beach for each 5°C increase in average temperature?
Flag reason: ibn SPR item has no machine-readable answer key in source data
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" alt="The figure presents a scatterplot titled “Number of Beach Visitors versus Temperature.” The horizontal axis is labeled “Average temperature, in degrees Celsius,” and the numbers 25 through 35, in increments of 2, are indicated. The vertical axis is labeled “Number of people,” and the numbers 0 through 640, in increments of 80, are indicated. There are 11 data points in the scatterplot that begin near the bottom left portion of the coordinate plane and trend upward and to the right. The line of best fit for the data is also shown. The line of best fit passes through the points with coordinates 25 comma 80 and 32 comma 480." /></p><p class="stem_paragraph ">
<br />
Each dot in the scatterplot above represents the temperature and the number of people who visited a beach in Lagos, Nigeria, on one of eleven different days. The line of best fit for the data is also shown. The line of best fit for the data has a slope of approximately 57. According to this estimate, how many additional people per day are predicted to visit the beach for each 5°C increase in average temperature?</p><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3171 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered) On May 10, 2015, there were 83 million Internet subscribers in Nigeria. The major Internet providers were MTN, Globacom, Airtel, Etisalat, and Visafone. By September 30, 2015, the number of Internet subscribers in Nigeria had increased to 97 million. If an Internet subscriber in Nigeria on September 30, 2015, is selected at random, the probability that the person selected was an MTN subscriber is 0.43. There were p p p million MTN subscribers in Nigeria on September 30, 2015. To the nearest integer, what is the value of p p p ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p class="stem_paragraph ">On May 10, 2015, there were 83 million Internet subscribers in Nigeria. The major Internet providers were MTN, Globacom, Airtel, Etisalat, and Visafone. By September 30, 2015, the number of Internet subscribers in Nigeria had increased to 97 million. If an Internet subscriber in Nigeria on September 30, 2015, is selected at random, the probability that the person selected was an MTN subscriber is 0.43. There were <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi></mrow><annotation encoding="application/x-tex">p</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">p</span></span></span></span> million MTN subscribers in Nigeria on September 30, 2015. To the nearest integer, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi></mrow><annotation encoding="application/x-tex">p</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">p</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3162 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
Which of the following statements correctly compares the means of data set A and data set B?
(A) The mean of each data set is 2.
(B) The mean of each data set is 4.
(C) The mean of data set A is less than the mean of data set B.
(D) The mean of data set A is greater than the mean of data set B.
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "Data set A is the set consisting of the following seven numbers: 1 comma 2, comma 3, comma 4, comma 5, comma 6, comma 7.
Data set B is the set consisting of the following seven numbers: 1 comma 1, comma 2, comma 2, comma 3, comma 3, comma 4.
": unexpected token: {"t":"word","v":"data","raw":"Data"}
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
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Data set B is the set consisting of the following seven numbers: 1 comma 1, comma 2, comma 2, comma 3, comma 3, comma 4.
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<p class="stem_paragraph ">Which of the following statements correctly compares the means of data set A and data set B?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3146 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered) Phone Email Dinner dance 55% 80% Football game 20% 10% Picnic 20% 5% Pool party 5% 5% Total 100% 100%
An alumni association survey asked each high school graduate to select the one activity he or she preferred for the association’s next event. Some of the people responded by phone, and the others responded by email. The table above shows the distribution of preferred activity, in percent, for each response type used.
For the survey, the number of email responses was twice the number of phone responses. If a person who preferred a picnic is selected at random, what is the probability that the person responded by email? Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="tcp-7a5447cc-f5d1-45b9-9203-029db2d5ded0"><table class="table_WithBorder tcp-fe7b2859-87f9-46d9-823c-53e153287cb2" style="width: 25%;"><thead><tr><td> </td><th class="tcp-8a553972-1312-4b68-938a-17ffd9a3fe54" scope="col">Phone</th><th class="tcp-4f072fa0-d80a-44ed-be0d-698503a06185" scope="col">Email</th></tr></thead><tbody><tr><th class="tcp-6cf71981-37f7-424d-a2d6-af4dfb847c74" scope="row">Dinner dance</th><td class="para_center tcp-2f2f59b4-6d9e-45ea-83f6-b6293536264d">55%</td><td class="para_center tcp-6046e0d7-b983-446a-bd00-755ea44caac7">80%</td></tr><tr><th class="tcp-453238ea-dfc3-460e-8ba9-f77581d59cbd" scope="row">Football game</th><td class="para_center tcp-009cecc7-9e5f-4b43-aadf-e15b6a392e6c">20%</td><td class="para_center tcp-7a538f4b-dc1e-49a4-bef0-4048e0ac7d54">10%</td></tr><tr><th class="tcp-60c57c44-ca42-4d4a-a1b5-cccee1a95d9e" scope="row">Picnic</th><td class="para_center tcp-2d5c1c22-3845-404f-98d3-2c941e481957">20%</td><td class="para_center tcp-881b4ee3-1685-4a30-b240-2350c612a3e7">5%</td></tr><tr><th class="tcp-361a3c23-b5e3-42f5-937c-d18a5153094c" scope="row">Pool party</th><td class="para_center tcp-6bf5fa34-9707-4ab0-8d8a-0b6a8cbc9aed">5%</td><td class="para_center tcp-a9a9f1ed-17f9-409a-99dc-06a99b68f7d1">5%</td></tr><tr><th class="tcp-8b8073fe-0c53-4c08-9958-9c142268cd27" scope="row">Total</th><td class="para_center tcp-89bbe0ba-97cf-45ec-9f88-306f64dc2189">100%</td><td class="para_center tcp-f172179d-b647-4601-9a67-a0a27994a49c">100%</td></tr></tbody></table><br />An alumni association survey asked each high school graduate to select the one activity he or she preferred for the association’s next event. Some of the people responded by phone, and the others responded by email. The table above shows the distribution of preferred activity, in percent, for each response type used. <span class="tcp-52eb63be-63dd-4d28-9c6e-9434bc369dcb">For the survey, the number of email responses was twice the number of phone responses. If a person who preferred a picnic is selected at random, what is the probability that the person responded by email?</span></div> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3132 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
The scatterplot above shows a company’s ice cream sales d d d , in dollars, and the high temperature t t t , in degrees Celsius (°C), on 12 different days. A line of best fit for the data is also shown. Which of the following could be an equation of the line of best fit?
(A) d = 0.03 t + 402 d = 0.03 t + 402 d = 0.03 t + 402
(B) d = 10 t + 402 d = 10 t + 402 d = 10 t + 402
(C) d = 33 t + 300 d = 33 t + 300 d = 33 t + 300
(D) d = 33 t + 84 d = 33 t + 84 d = 33 t + 84
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "": empty alt text
Corrected stem text <div class="stimulus_reference ">
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" alt="The figure presents a scatterplot titled “Ice Cream Sales.” The horizontal axis is labeled “Temperature, in degrees Celsius,” and the integers 10 through 26, in increments of 2, are indicated. The vertical axis is labeled “Sales, in dollars,” and the integers 300 through 1,000, in increments of 100, are indicated. There are 12 data points in the scatterplot, and the line of best fit is drawn. The line of best fit begins slightly above the horizontal axis, and slightly to the right of the vertical axis, and slants upward and to the right. It passes through the point 12 comma 480 and the point 24 comma 880." /></div>
</div>
<p class="stem_paragraph ">The scatterplot above shows a company’s ice cream sales <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>d</mi></mrow><annotation encoding="application/x-tex">d</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">d</span></span></span></span>, in dollars, and the high temperature <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span>, in degrees Celsius (°C), on 12 different days. A line of best fit for the data is also shown. Which of the following could be an equation of the line of best fit?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #3124 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3113 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
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Question #3110 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered) International Tourist Arrivals, in millionsCountry 2012 2013 France 83.0 84.7 United States 66.7 69.8 Spain 57.5 60.7 China 57.7 55.7 Italy 46.4 47.7 Turkey 35.7 37.8 Germany 30.4 31.5 United Kingdom 26.3 32.2 Russia 24.7 28.4
The table above shows the number of international tourist arrivals, rounded to the nearest tenth of a million, to the top nine tourist destinations in both 2012 and 2013. Based on the information given in the table, how much greater, in millions, was the median number of international tourist arrivals to the top nine tourist destinations in 2013 than the median number in 2012, to the nearest tenth of a million?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="tcp-d0c2309e-cff2-4e20-8812-f77647f284f7"><table class="table_WithBorder tcp-879172e5-51cf-43dd-ae53-1077f3c99822" style="width: 25%;">International Tourist Arrivals, in millions<thead><tr><th class="tcp-560208f3-ac65-4942-af78-f8d3f19fad57 para_center" scope="col" style="text-align: center; vertical-align: middle;">Country</th><th class="tcp-de86673f-5829-4cdc-bca0-66992cf45275 para_center" scope="col" style="text-align: center; vertical-align: middle;">2012</th><th class="tcp-2902b735-1dd8-42d3-af08-9f35a5dccb08 para_center" scope="col" style="text-align: center; vertical-align: middle;">2013</th></tr></thead><tbody><tr><th class="tcp-c893c7f3-7807-467b-895a-c513d67bf251" scope="row">France</th><td class="tcp-a56ded3d-873a-4755-8bdc-13c5cc107b6a para_center" style="text-align: center; vertical-align: middle;">83.0</td><td class="tcp-16bf8d9c-10a0-46be-874b-12f701512dde para_center" style="text-align: center; vertical-align: middle;">84.7</td></tr><tr><th class="tcp-fb8068fc-a892-43f0-b19b-74b5602fe968" scope="row">United States</th><td class="tcp-361a51ef-d99d-4ef9-8997-f38216bd4c4b para_center" style="text-align: center; vertical-align: middle;">66.7</td><td class="tcp-e290f68d-a499-408d-a8e6-00a39550cbd4 para_center" style="text-align: center; vertical-align: middle;">69.8</td></tr><tr><th class="tcp-b2685fd1-c8fc-47e5-bf4b-d4890b4c4cd1" scope="row">Spain</th><td class="tcp-ec8d22ee-041a-4f83-8f0e-d5bf5e266716 para_center" style="text-align: center; vertical-align: middle;">57.5</td><td class="tcp-0683eedd-238b-4251-870c-5d61e97ac005 para_center" style="text-align: center; vertical-align: middle;">60.7</td></tr><tr><th class="tcp-9b51d6b9-74c9-4d6b-a565-bca1da1f6b1d" scope="row">China</th><td class="tcp-9efcf4b3-7a57-4007-abc0-3b53348b1fef para_center" style="text-align: center; vertical-align: middle;">57.7</td><td class="tcp-43dd7a81-a876-4ada-9b9a-e0e8ba063213 para_center" style="text-align: center; vertical-align: middle;">55.7</td></tr><tr><th class="tcp-c26ba1fd-c333-4003-b456-2eb9be91fbd0" scope="row">Italy</th><td class="tcp-0cd35d66-5bb1-4b13-a001-b92af56ddf08 para_center" style="text-align: center; vertical-align: middle;">46.4</td><td class="tcp-2a3215d2-3015-40f6-8350-784f79daa9da para_center" style="text-align: center; vertical-align: middle;">47.7</td></tr><tr><th class="tcp-db071184-27fc-407a-94a3-bb3788236128" scope="row">Turkey</th><td class="tcp-abf5db52-e9a0-486e-9827-4be6a69db3b3 para_center" style="text-align: center; vertical-align: middle;">35.7</td><td class="tcp-57b77ab9-7012-4177-8658-3a18bd061e2b para_center" style="text-align: center; vertical-align: middle;">37.8</td></tr><tr><th class="tcp-87d199b0-d793-4e53-a57f-67b53ed3a06e" scope="row">Germany</th><td class="tcp-c268d6f7-eeba-4124-9209-ddac5ac973a6 para_center" style="text-align: center; vertical-align: middle;">30.4</td><td class="tcp-2845c9a3-17bc-4981-9f8a-ad75f7aa238e para_center" style="text-align: center; vertical-align: middle;">31.5</td></tr><tr><th class="tcp-f0793ddb-5c72-45fb-b174-383f1a06dc68" scope="row">United Kingdom</th><td class="tcp-8cc5091d-85ae-4d0e-8ce1-4718d3275bd1 para_center" style="text-align: center; vertical-align: middle;">26.3</td><td class="tcp-b3b899d7-5d19-48e3-8d03-5139c5e7b647 para_center" style="text-align: center; vertical-align: middle;">32.2</td></tr><tr><th class="tcp-c7ccc4a1-f59d-4b24-b27a-57aaade9c422" scope="row">Russia</th><td class="tcp-e20a824b-0901-4ecf-8336-a69c65f4f7ca para_center" style="text-align: center; vertical-align: middle;">24.7</td><td class="tcp-f1c8fe7d-7094-4401-b12d-9b7795d4dd8c para_center" style="text-align: center; vertical-align: middle;">28.4</td></tr></tbody></table><p class="stem_paragraph ">The table above shows the number of international tourist arrivals, rounded to the nearest tenth of a million, to the top nine tourist destinations in both 2012 and 2013. Based on the information given in the table, how much greater, in millions, was the median number of international tourist arrivals to the top nine tourist destinations in 2013 than the median number in 2012, to the nearest tenth of a million?</p><div id="level-access-access-assistant-highlight-container"> </div></div> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3104 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered) On April 18, 1775, Paul Revere set off on his midnight ride from Charlestown to Lexington. If he had ridden straight to Lexington without stopping, he would have traveled 11 miles in 26 minutes. In such a ride, what would the average speed of his horse have been, to the nearest tenth of a mile per hour ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 3 math-img alt-text failed MathSpeak conversion: "Average speed equals, the fraction 11 miles over 26 minutes, end fraction, times, the fraction 60 minutes over 1 hour, end fraction": unexpected token: {"t":"word","v":"average","raw":"Average"} | "which equals, the fraction 660 over 26, end fraction, miles per hour": unexpected token: {"t":"word","v":"which","raw":"which"} | "which is approximately equal to 25 point 3 8 miles per hour": unexpected token: {"t":"word","v":"which","raw":"which"}
Corrected stem text <p class="stem_paragraph ">On April 18, 1775, Paul Revere set off on his midnight ride from Charlestown to Lexington. If he had ridden straight to Lexington without stopping, he would have traveled 11 miles in 26 minutes. In such a ride, what would the average speed of his horse have been, to the nearest tenth of a mile per <u><span class="underline"><span class="underline ">hour</span></span></u>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3089 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered) Which of the following is true about the values of 2 x 2^{x} 2 x and 2 x + 2 2 x + 2 2 x + 2 for x > 0 x > 0 x > 0 ?
(A) For all x > 0 x > 0 x > 0 , it is true that 2 x < 2 x + 2 2^{x} < 2 x + 2 2 x < 2 x + 2 .
(B) For all x > 0 x > 0 x > 0 , it is true that 2 x > 2 x + 2 2^{x} > 2 x + 2 2 x > 2 x + 2 .
(C) There is a constant c c c such that if 0 < x < c 0 < x < c 0 < x < c , then 2 x < 2 x + 2 2^{x} < 2 x + 2 2 x < 2 x + 2 , but if x > c x > c x > c , then 2 x > 2 x + 2 2^{x} > 2 x + 2 2 x > 2 x + 2 .
(D) There is a constant c c c such that if 0 < x < c 0 < x < c 0 < x < c , then 2 x > 2 x + 2 2^{x} > 2 x + 2 2 x > 2 x + 2 , but if x > c x > c x > c , then 2 x < 2 x + 2 2^{x} < 2 x + 2 2 x < 2 x + 2 .
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "2 x plus 2, where 2 to the 0 power is less than, 2 times 0, plus 2": leftover tokens: [{"t":"word","v":"where","raw":"where"},{"t":"num","v":"2"},{"t":"word","v":"to","raw":"to"},{"t":"word","v":"the","raw":"the"},{"t":"num","v":"0"},{"t":"word","v":"power","raw":"power"},{"t":"word","v":"is","raw":"is"},{"t":"word","v":"less","raw":"less"},{"t":"word","v":"than","raw":"than"},{"t":"comma","v":","},{"t":"num","v":"2"},{"t":"word","v":"times","raw":"times"},{"t":"num","v":"0"},{"t":"comma","v":","},{"t":"word","v":"plus","raw":"plus"},{"t":"num","v":"2"}]
Corrected stem text <p class="stem_paragraph ">Which of the following is true about the values of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mn>2</mn><mi>x</mi></msup></mrow><annotation encoding="application/x-tex">2^{x}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6644em;"></span><span class="mord"><span class="mord">2</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6644em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">x</span></span></span></span></span></span></span></span></span></span></span></span></span></span> and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn><mi>x</mi><mo>+</mo><mn>2</mn></mrow><annotation encoding="application/x-tex">2 x + 2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">2</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2</span></span></span></span></span></span> for <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>></mo><mn>0</mn></mrow><annotation encoding="application/x-tex">x > 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.5782em;vertical-align:-0.0391em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">></span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #3074 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3069 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Currently stored (rendered)
The line graph shows the total amount of snow, in inches, recorded each year in Washington, DC, from 2003 to 2015. If p % p\% p % is the percent decrease in the annual snowfall from 2003 to 2007, what is the value ofp p p ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p><img 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" alt="The figure presents a line graph. The horizontal axis is labeled “Year,” and the years 2003 through 2015 are indicated. The vertical axis is labeled “Annual snowfall, in inches,” and the numbers 0 through 60, in increments of 10, are indicated. There are 13 points indicated on the graph. The data represented by the 13 points are as follows. Note that all values are approximate. Year, 2003. Number of inches, 40. Year, 2004. Number of inches, 12. Year, 2005. Number of inches, 13. Year, 2006. Number of inches, 14. Year, 2007. Number of inches, 10. Year, 2008. Number of inches, 5. Year, 2009. Number of inches, 8. Year, 2010. Number of inches, 56. Year, 2011. Number of inches, 10. Year, 2012. Number of inches, 3. Year, 2013. Number of inches, 4. Year, 2014. Number of inches, 32. Year, 2015. Number of inches, 19." /></p><p class="stem_paragraph ">
<br />
The line graph shows the total amount of snow, in inches, recorded each year in Washington, DC, from 2003 to 2015. If <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">p\%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.9444em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">p</span><span class="mord">%</span></span></span></span></span></span> is the percent decrease in the annual snowfall from 2003 to 2007, what is the value of<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi></mrow><annotation encoding="application/x-tex">p</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">p</span></span></span></span>?</p><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3068 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
Data set A and data set B each contain 5 numbers. If the mean of data set A is equal to the mean of data set B, what is the value of x x x ?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "Data set A consists of the 5 numbers: 72, 73, 73, 76, and 76. Data set B consists of the 5 numbers: 61, 64, 74, 85, and x.": unexpected token: {"t":"word","v":"data","raw":"Data"}
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="Data set A consists of the 5 numbers: 72, 73, 73, 76, and 76. Data set B consists of the 5 numbers: 61, 64, 74, 85, and x." /></span></p>
</div>
<p class="stem_paragraph ">Data set A and data set B each contain 5 numbers. If the mean of data set A is equal to the mean of data set B, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3066 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3065 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
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Question #3054 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
Currently stored (rendered) A group of monarch butterflies migrated from Chicago, Illinois, to Michoacán, Mexico, flying a total of 2,100 miles. It took a single butterfly in the group 120 days to travel this route one way. On average, how many miles did the butterfly travel per day?
Flag reason: no correct_choice in source data
Corrected stem text <p class="stem_paragraph ">A group of monarch butterflies migrated from Chicago, Illinois, to Michoacán, Mexico, flying a total of 2,100 miles. It took a single butterfly in the group 120 days to travel this route one way. On average, how many miles did the butterfly travel per day?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3044 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3042 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered)
What is the median of the seven data values shown?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "The seven data values 2, 2, 2, 3, 4, 4, 11 are shown.": leftover tokens: [{"t":"word","v":"data","raw":"data"},{"t":"word","v":"values","raw":"values"},{"t":"num","v":"2"},{"t":"comma","v":","},{"t":"num","v":"2"},{"t":"comma","v":","},{"t":"num","v":"2"},{"t":"comma","v":","},{"t":"num","v":"3"},{"t":"comma","v":","},{"t":"num","v":"4"},{"t":"comma","v":","},{"t":"num","v":"4"},{"t":"comma","v":","},{"t":"num","v":"11"},{"t":"word","v":"are","raw":"are"},{"t":"word","v":"shown","raw":"shown"}]
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAHgAAAAWCAYAAAALmlj4AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAABGJhU0UAAAALV/ZLFgAAAAFzUkdCAK7OHOkAAAAEZ0FNQQAAsY8L/GEFAAABsklEQVRoQ+2XC46EIAxAPR4H4jjcxat4E5ZSq/hBS2lGNulLjOMuPKGtHWcCYlxicFOEj3S4sMCZzSgOYPalw8WkaHYQcQnRpZOfv3XAnt5icTtmD6qP6f75n3H2cGYHdxQHgMk9O+RJpmLpTU46iR2cOFTHYHVdA7AEl673QD0xluMYSCqcliIhKGhw9CYHDokD94/za3vgjLmAC+MFtsYIjq0zpOiuf2JB83yQt9deB+4din6OPl3eJY8z5pbcVlxIS5QnZwQHVve1M7yR58F9O74/NRxATOX9ljzOmA2sCvmCgK8dZdtqnU/BgnnSFyQNB6GaYApqa0srGcUBUHBbPLlrrOOlydFwEGoJ3qq+IRhnRnGUoI/XpjEZ+1hJcjQcJSoJzhX3InljFMcZ7Aa8BJet/Xr8zlHSnWBaUE9QR3DUvrPRK3sT7336gE+fYLp5T2KGcaw/S8q3bkq61PvvE/zcTvaqz+MqP1dGcQBbkov5t0/0g6OklpxfOroSzCUHzvM2VMMcRzQcauQqTCW4XoowxxENhxrQTtJauhZjjiMaDsMwDMMwDMMwDKOBafoDiu9bgG/l4I0AAAAASUVORK5CYII=" alt="The seven data values 2, 2, 2, 3, 4, 4, 11 are shown." /></span></p>
</div>
<p class="stem_paragraph ">What is the median of the seven data values shown?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3041 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
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Question #3039 · Question bank · math · Problem-Solving and Data Analysis · type: mcqno answer key
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Question #3037 · Question bank · math · Problem-Solving and Data Analysis · type: mcq
Currently stored (rendered) The International Space Station orbits Earth at an average speed of 4.76 miles per second. What is the space station’s average speed in miles per hour ?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "the fraction with numerator 4 point 7 6 miles, and denominator second, times, the fraction with numerator 3,600 seconds, and denominator hour, equals, the fraction with numerator 17,136 miles, and denominator hour": unexpected token: {"t":"word","v":"hour","raw":"hour"}
Corrected stem text <p class="stem_paragraph ">The International Space Station orbits Earth at an average speed of 4.76 miles per second. What is the space station’s average speed in miles per <span class="underline"><span class="formatted_text text_decoration:underline ">hour</span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3032 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Source PDF page (reference) No source page on record.
Question #3023 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered)
x + 4 = 11 \sqrt{x + 4} = 11 x + 4 = 11
What value of x x x satisfies the equation above?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msqrt><mrow><mi>x</mi><mo>+</mo><mn>4</mn></mrow></msqrt><mo>=</mo><mn>11</mn></mrow><annotation encoding="application/x-tex">\sqrt{x + 4} = 11</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1744em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.8656em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">4</span></span></span><span style="top:-2.8256em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1744em;"><span></span></span></span></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">11</span></span></span></span></span></span>
</p>
</div>
<p class="stem_paragraph ">What value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> satisfies the equation above?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #3022 · Question bank · math · Advanced Math · type: mcq
Currently stored (rendered) Let the function p p p be defined as p ( x ) = ( x − c ) 2 + 160 2 c p(x) = \dfrac{\left(x - c\right)^2 + 160}{2 c} p ( x ) = 2 c ( x − c ) 2 + 160 , where c c c is a constant. If p ( c ) = 10 p(c) = 10 p ( c ) = 10 , what is the value of p ( 12 ) p(12) p ( 12 ) ?
Flag reason: 2 math-img alt-text failed MathSpeak conversion: "which equals the fraction with numerator 16 plus 160, and denominator 16": unexpected token: {"t":"word","v":"which","raw":"which"} | "which equals 11": unexpected token: {"t":"word","v":"which","raw":"which"}
Corrected stem text <p class="stem_paragraph ">Let the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi></mrow><annotation encoding="application/x-tex">p</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">p</span></span></span></span> be defined as <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><msup><mrow><mo fence="true">(</mo><mi>x</mi><mo>−</mo><mi>c</mi><mo fence="true">)</mo></mrow><mn>2</mn></msup><mo>+</mo><mn>160</mn></mrow><mrow><mn>2</mn><mi>c</mi></mrow></mfrac></mstyle></mrow><annotation encoding="application/x-tex">p(x) = \dfrac{\left(x - c\right)^2 + 160}{2 c}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">p</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.317em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.631em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">2</span><span class="mord mathnormal">c</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord mathnormal">c</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.954em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">160</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span> is a constant. <span class="formatted_line_break delivery_mode:PPT "></span>If <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo stretchy="false">(</mo><mi>c</mi><mo stretchy="false">)</mo><mo>=</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">p(c) = 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">p</span><span class="mopen">(</span><span class="mord mathnormal">c</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></span></span>, what is the value of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>p</mi><mo stretchy="false">(</mo><mn>12</mn><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">p(12)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">p</span><span class="mopen">(</span><span class="mord">12</span><span class="mclose">)</span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #2982 · Question bank · math · Advanced Math · type: mcq
Currently stored (rendered) If a a a and c c c are positive numbers, which of the following is equivalent to ( a + c ) 3 × a + c \sqrt{\left(a + c\right)^3} \times \sqrt{a + c} ( a + c ) 3 × a + c ?
(C)
a 2 + 2 a c + c 2 a^2 + 2 a c + c^2 a 2 + 2 a c + c 2
Flag reason: 2 math-img alt-text failed MathSpeak conversion: "the square root of, open parenthesis, a, plus c, close parenthesis, cubed, end root, times, the square root of a, plus c, end root, equals the square root of, open parenthesis a, plus c, end parenthesis to the power 4, end root": expected 'close parenthesis' | "the square root of, open outer parenthesis, open inner parenthesis, a, plus c, close inner parenthesis, squared, close outer parenthesis, squared, end root, equals, open parenthesis, a, plus c, close parenthesis, squared, which equals a, squared, plus 2 a, c, plus c squared": unexpected token: {"t":"word","v":"open","raw":"open"}
Corrected stem text <p class="stem_paragraph ">If <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span> are positive numbers, which of the following is equivalent to <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msqrt><msup><mrow><mo fence="true">(</mo><mi>a</mi><mo>+</mo><mi>c</mi><mo fence="true">)</mo></mrow><mn>3</mn></msup></msqrt><mo>×</mo><msqrt><mrow><mi>a</mi><mo>+</mo><mi>c</mi></mrow></msqrt></mrow><annotation encoding="application/x-tex">\sqrt{\left(a + c\right)^3} \times \sqrt{a + c}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.84em;vertical-align:-0.503em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.337em;"><span class="svg-align" style="top:-3.8em;"><span class="pstrut" style="height:3.8em;"></span><span class="mord" style="padding-left:1em;"><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">a</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord mathnormal">c</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.954em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">3</span></span></span></span></span></span></span></span></span></span><span style="top:-3.297em;"><span class="pstrut" style="height:3.8em;"></span><span class="hide-tail" style="min-width:1.02em;height:1.88em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.88em" viewBox="0 0 400000 1944" preserveAspectRatio="xMinYMin slice"><path d="M983 90
l0 -0
c4,-6.7,10,-10,18,-10 H400000v40
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c-10,12,-21,25,-33,39s-32,39,-32,39c-6,-5.3,-15,-14,-27,-26s25,-30,25,-30
c26.7,-32.7,52,-63,76,-91s52,-60,52,-60s208,722,208,722
c56,-175.3,126.3,-397.3,211,-666c84.7,-268.7,153.8,-488.2,207.5,-658.5
c53.7,-170.3,84.5,-266.8,92.5,-289.5z
M1001 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.503em;"><span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.205em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.835em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal">a</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord mathnormal">c</span></span></span><span style="top:-2.795em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
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c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.205em;"><span></span></span></span></span></span></span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2977 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered)
h ( x ) = x 3 + a x 2 + b x + c h(x) = x^3 + a x^2 + b x + c h ( x ) = x 3 + a x 2 + b x + c
The function h h h is defined above, where a a a , b b b , and c c c are integer constants. If the zeros of the function are − 5 -5 − 5 6, and 7, what is the value of c c c ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo><mo>=</mo><msup><mi>x</mi><mn>3</mn></msup><mo>+</mo><mi>a</mi><msup><mi>x</mi><mn>2</mn></msup><mo>+</mo><mi>b</mi><mi>x</mi><mo>+</mo><mi>c</mi></mrow><annotation encoding="application/x-tex">h(x) = x^3 + a x^2 + b x + c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">h</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">3</span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">a</span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.7778em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">b</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span></span></span>
</p>
</div>
<p class="stem_paragraph ">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi></mrow><annotation encoding="application/x-tex">h</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">h</span></span></span></span> is defined above, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span> are integer constants. If the zeros of the function are <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>−</mo><mn>5</mn></mrow><annotation encoding="application/x-tex">-5</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord">5</span></span></span></span></span></span> 6, and 7, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2966 · Question bank · math · Advanced Math · type: mcq
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Question #2965 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered) The total distance d d d , in meters, traveled by an object moving in a straight line can be modeled by a quadratic function that is defined in terms of t t t , where t t t is the time in seconds. At a time of 10.0 seconds, the total distance traveled by the object is 50.0 meters, and at a time of 20.0 seconds, the total distance traveled by the object is 200.0 meters. If the object was at a distance of 0 meters when t = 0 t = 0 t = 0 , then what is the total distance traveled, in meters, by the object after 30.0 seconds?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p class="stem_paragraph ">The total distance <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>d</mi></mrow><annotation encoding="application/x-tex">d</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">d</span></span></span></span>, in meters, traveled by an object moving in a straight line can be modeled by a quadratic function that is defined in terms of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> is the time in seconds. At a time of 10.0 seconds, the total distance traveled by the object is 50.0 meters, and at a time of 20.0 seconds, the total distance traveled by the object is 200.0 meters. If the object was at a distance of 0 meters when <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">t = 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span></span></span>, then what is the total distance traveled, in meters, by the object after 30.0 seconds?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2952 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2949 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2929 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered) In thex y xy x y -plane, the graph of y = 3 x 2 − 14 x y = 3 x^2 - 14 x y = 3 x 2 − 14 x intersects the graph of y = x y = x y = x at the points ( 0 , 0 ) \left(0, 0\right) ( 0 , 0 ) and a , a a, a a , a . What is the value of a a a ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p class="stem_paragraph ">In the<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane, the graph of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mn>3</mn><msup><mi>x</mi><mn>2</mn></msup><mo>−</mo><mn>14</mn><mi>x</mi></mrow><annotation encoding="application/x-tex">y = 3 x^2 - 14 x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord">3</span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">14</span><span class="mord mathnormal">x</span></span></span></span></span></span> intersects the graph of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>x</mi></mrow><annotation encoding="application/x-tex">y = x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span></span></span> at the points <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mn>0</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0, 0\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">0</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span> and <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><mo separator="true">,</mo><mi>a</mi></mrow><annotation encoding="application/x-tex">a, a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">a</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal">a</span></span></span></span></span><span class="math_expression "></span>. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #2925 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2922 · Question bank · math · Advanced Math · type: mcqno answer key
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Question #2919 · Question bank · math · Advanced Math · type: mcq
Currently stored (rendered) The surface area of a cube is 6 × ( a 4 ) 2 6 \times \left(\dfrac{a}{4}\right)^2 6 × ( 4 a ) 2 , where a a a is a positive constant. Which of the following gives the perimeter of one face of the cube?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "6 times, open parenthesis, the fraction with numerator a, over 4, and denominator 4, close parenthesis, squared, equals, 6 times, open parenthesis, a, over 16, close parenthesis, squared": unexpected token: {"t":"word","v":"denominator","raw":"denominator"}
Corrected stem text <p class="stem_paragraph ">The surface area of a cube is <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><mo>×</mo><msup><mrow><mo fence="true">(</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mi>a</mi><mn>4</mn></mfrac></mstyle><mo fence="true">)</mo></mrow><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">6 \times \left(\dfrac{a}{4}\right)^2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">6</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:2.04em;vertical-align:-0.686em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;"><span class="delimsizing size2">(</span></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.1076em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">4</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">a</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mclose delimcenter" style="top:0em;"><span class="delimsizing size2">)</span></span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:1.354em;"><span style="top:-3.6029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> is a positive constant. Which of the following gives the perimeter of one face of the cube?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2907 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2906 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2890 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2831 · Question bank · math · Advanced Math · type: grid_inno answer key
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The graph of the function f f f , defined by f ( x ) = − 1 2 × ( x − 4 ) 2 + 10 f(x) = -\dfrac{1}{2} \times \left(x - 4\right)^2 + 10 f ( x ) = − 2 1 × ( x − 4 ) 2 + 10 , is shown in the x y xy x y -plane above. If the function g g g (not shown) is defined by g ( x ) = − x + 10 g(x) = -x + 10 g ( x ) = − x + 10 , what is one possible value of a a a such that f ( a ) = g ( a ) f(a) = g(a) f ( a ) = g ( a ) ?
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" alt="The figure presents the graph of a curve in the xy-plane. The curve is labeled y equals f of x. The numbers 0 through 9 are indicated on the x-axis. The numbers 0 through 12, in increments of 2, are indicated on the y-axis. The curve begins at the point with coordinates 0 comma 2 and moves upward and to the right reaching a maximum at the point with coordinates 4 comma 10. It turns and moves downward and to the right, ending at 8 point 5 on the x-axis" /></div>
</div>
<p class="stem_paragraph ">The graph of the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>, defined by <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo><mo>=</mo><mo>−</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>1</mn><mn>2</mn></mfrac></mstyle><mo>×</mo><msup><mrow><mo fence="true">(</mo><mi>x</mi><mo>−</mo><mn>4</mn><mo fence="true">)</mo></mrow><mn>2</mn></msup><mo>+</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">f(x) = -\dfrac{1}{2} \times \left(x - 4\right)^2 + 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord">−</span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">2</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">1</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.204em;vertical-align:-0.25em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">4</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.954em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></span></span>, is shown in the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane above. If the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi></mrow><annotation encoding="application/x-tex">g</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span></span></span></span> (not shown) is defined by <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo><mo>=</mo><mo>−</mo><mi>x</mi><mo>+</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">g(x) = -x + 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></span></span>, what is one possible value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> such that <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mo stretchy="false">(</mo><mi>a</mi><mo stretchy="false">)</mo><mo>=</mo><mi>g</mi><mo stretchy="false">(</mo><mi>a</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">f(a) = g(a)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mopen">(</span><span class="mord mathnormal">a</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span><span class="mopen">(</span><span class="mord mathnormal">a</span><span class="mclose">)</span></span></span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
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Question #2828 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2826 · Question bank · math · Advanced Math · type: mcq
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Question #2812 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2794 · Question bank · math · Advanced Math · type: grid_inno answer key
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Question #2762 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered) During a 5-second time interval, the average acceleration a a a , in meters per second squared, of an object with an initial velocity of 12 meters per second is defined by the equation a = v f − 12 5 a = \dfrac{v_{f} - 12}{5} a = 5 v f − 12 , where v v v f f f is the final velocity of the object in meters per second. If the equation is rewritten in the form v f v_{f} v f = x a xa x a + y y y , where x x x and y y y are constants, what is the value of x x x ?
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Corrected stem text <p class="stem_paragraph ">During a 5-second time interval, the average acceleration <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span>, in meters per second squared, of an object with an initial velocity of 12 meters per second is defined by the equation <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><msub><mi>v</mi><mi>f</mi></msub><mo>−</mo><mn>12</mn></mrow><mn>5</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">a = \dfrac{v_{f} - 12}{5}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">5</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord"><span class="mord mathnormal" style="margin-right:0.0359em;">v</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3361em;"><span style="top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.1076em;">f</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.2861em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">12</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>v</mi></mrow><annotation encoding="application/x-tex">v</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">v</span></span></span></span><sub><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span></sub> is the final velocity of the object in meters per second. If the equation is rewritten in the form <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub><mi>v</mi><mi>f</mi></msub></mrow><annotation encoding="application/x-tex">v_{f}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7167em;vertical-align:-0.2861em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0359em;">v</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3361em;"><span style="top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.1076em;">f</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.2861em;"><span></span></span></span></span></span></span></span></span></span> = <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>a</mi></mrow><annotation encoding="application/x-tex">xa</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal">a</span></span></span></span> + <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span> are constants, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2752 · Question bank · math · Advanced Math · type: grid_inno answer key
Currently stored (rendered) If x 5 x 4 3 = x a b \dfrac{\sqrt{x^{5}}}{\sqrt[3]{x^{4}}} = x^{\dfrac{a}{b}} 3 x 4 x 5 = x b a for all positive values of x x x , what is the value of a b \dfrac{a}{b} b a ?
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Corrected stem text <p class="stem_paragraph ">If <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><msqrt><msup><mi>x</mi><mn>5</mn></msup></msqrt><mroot><msup><mi>x</mi><mn>4</mn></msup><mn>3</mn></mroot></mfrac></mstyle><mo>=</mo><msup><mi>x</mi><mstyle scriptlevel="0" displaystyle="true"><mfrac><mi>a</mi><mi>b</mi></mfrac></mstyle></msup></mrow><annotation encoding="application/x-tex">\dfrac{\sqrt{x^{5}}}{\sqrt[3]{x^{4}}} = x^{\dfrac{a}{b}}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:2.5621em;vertical-align:-0.93em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.6321em;"><span style="top:-2.1549em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord sqrt"><span class="root"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8443em;"><span style="top:-3.0221em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size6 size1 mtight"><span class="mord mtight"><span class="mord mtight">3</span></span></span></span></span></span></span></span><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9551em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.7401em;"><span style="top:-2.989em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">4</span></span></span></span></span></span></span></span></span></span></span><span style="top:-2.9151em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.0849em;"><span></span></span></span></span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.93em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1.9013em;"></span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:1.9013em;"><span style="top:-3.9013em;margin-right:0.05em;"><span class="pstrut" style="height:3.1076em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord sizing reset-size3 size6"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.1076em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">b</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">a</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span> for all positive values of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span>, what is the value of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mi>a</mi><mi>b</mi></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\dfrac{a}{b}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.7936em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.1076em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">b</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal">a</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2733 · Question bank · math · Advanced Math · type: mcq
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Question #2701 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2692 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2688 · Question bank · math · Algebra · type: grid_inno answer key
Currently stored (rendered)
5 x + 3 y = 38 and x + 3 y = 10 5 x + 3 y = 38\ \text{and}\ x + 3 y = 10 5 x + 3 y = 38 and x + 3 y = 10
In the solution x , y x, y x , y to the system of equations above, what is the value of x x x ?
Flag reason: ibn SPR item has no machine-readable answer key in source data; 1 math-img alt-text failed MathSpeak conversion: "Equation 1, 5 x, plus 3 y, equals 38; Equation 2, x plus 3 y, equals 10; Subtracting equation 2 from equation 1 yields equation 3, which is 4 x, equals 28.": leftover tokens: [{"t":"word","v":"subtracting","raw":"Subtracting"},{"t":"word","v":"equation","raw":"equation"},{"t":"num","v":"2"},{"t":"word","v":"from","raw":"from"},{"t":"word","v":"equation","raw":"equation"},{"t":"num","v":"1"},{"t":"word","v":"yields","raw":"yields"}]
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>5</mn><mi>x</mi><mo>+</mo><mn>3</mn><mi>y</mi><mo>=</mo><mn>38</mn><mtext> and </mtext><mi>x</mi><mo>+</mo><mn>3</mn><mi>y</mi><mo>=</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">5 x + 3 y = 38\ \text{and}\ x + 3 y = 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">5</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">3</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7778em;vertical-align:-0.0833em;"></span><span class="mord">38</span><span class="mspace"> </span><span class="mord text"><span class="mord">and</span></span><span class="mspace"> </span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">3</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></span></span>
</p>
</div>
<p class="stem_paragraph ">In the solution <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo separator="true">,</mo><mi>y</mi></mrow><annotation encoding="application/x-tex">x, y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span></span></span> to the system of equations above, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2687 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2686 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2680 · Question bank · math · Algebra · type: mcqno answer key
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Question #2665 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2655 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2652 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2649 · Question bank · math · Algebra · type: mcqno answer key
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Question #2625 · Question bank · math · Algebra · type: mcq
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Question #2620 · Question bank · math · Algebra · type: mcq
Currently stored (rendered) On January 1, 2015, a city’s minimum hourly wage was $9.25. It will increase by $0.50 on the first day of the year for the next 5 years. Which of the following functions best models the minimum hourly wage, in dollars, x x x years after January 1, 2015, where ?
(A)
f ( x ) = 9.25 − 0.50 x f(x) = 9.25 - 0.50 x f ( x ) = 9.25 − 0.50 x
(B)
f ( x ) = 9.25 x − 0.50 f(x) = 9.25 x - 0.50 f ( x ) = 9.25 x − 0.50
(C)
f ( x ) = 9.25 + 0.50 x f(x) = 9.25 + 0.50 x f ( x ) = 9.25 + 0.50 x
(D)
f ( x ) = 9.25 x + 0.50 f(x) = 9.25 x + 0.50 f ( x ) = 9.25 x + 0.50
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "x equals the following five values: 1, 2, 3, 4, 5": unexpected token: {"t":"word","v":"following","raw":"following"}
Corrected stem text <p class="stem_paragraph ">On January 1, 2015, a city’s minimum hourly wage was $9.25. It will increase by $0.50 on the first day of the year for the next 5 years. Which of the following functions best models the minimum hourly wage, in dollars, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> years after January 1, 2015, where <span class="math_expression "><span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="x equals the following five values: 1, 2, 3, 4, 5" /></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2607 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2601 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2585 · Question bank · math · Algebra · type: grid_inno answer key
Currently stored (rendered)
I = V R I = \dfrac{V}{R} I = R V
The formula above is Ohm’s law for an electric circuit with current I I I , in amperes, potential difference V V V , in volts, and resistance R R R , in ohms. A circuit has a resistance of 500 ohms, and its potential difference will be generated by n n n six-volt batteries that produce a total potential difference of 6 n 6 n 6 n volts. If the circuit is to have a current of no more than 0.25 ampere, what is the greatest number, n n n , of six-volt batteries that can be used?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 "><span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>I</mi><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mi>V</mi><mi>R</mi></mfrac></mstyle></mrow><annotation encoding="application/x-tex">I = \dfrac{V}{R}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0785em;">I</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0463em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3603em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.2222em;">V</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span></span></p>
</div>
<p class="stem_paragraph ">The formula above is Ohm’s law for an electric circuit with current <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>I</mi></mrow><annotation encoding="application/x-tex">I</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0785em;">I</span></span></span></span>, in amperes, potential difference <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>V</mi></mrow><annotation encoding="application/x-tex">V</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.2222em;">V</span></span></span></span>, in volts, and resistance <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi></mrow><annotation encoding="application/x-tex">R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span>, in ohms. A circuit has a resistance of 500 ohms, and its potential difference will be generated by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span> six-volt batteries that produce a total potential difference of <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><mi>n</mi></mrow><annotation encoding="application/x-tex">6 n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">6</span><span class="mord mathnormal">n</span></span></span></span></span></span> volts. If the circuit is to have a current of no more than 0.25 ampere, what is the greatest number, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span>, of six-volt batteries that can be used?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2580 · Question bank · math · Algebra · type: mcq
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Question #2571 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2563 · Question bank · math · Algebra · type: mcq
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Question #2559 · Question bank · math · Algebra · type: mcq
Currently stored (rendered) Townsend Realty Group InvestmentsProperty address Purchase price (dollars) Monthly rental price (dollars) Clearwater Lane 128,000 950 Driftwood Drive 176,000 1,310 Edgemont Street 70,000 515 Glenview Street 140,000 1,040 Hamilton Circle 450,000 3,365
The Townsend Realty Group invested in the five different properties listed in the table above. The table shows the amount, in dollars, the company paid for each property and the corresponding monthly rental price, in dollars, the company charges for the property at each of the five locations. Townsend Realty purchased the Glenview Street property and received a 40% discount off the original price along with an additional 20% off the discounted price for purchasing the property in cash. Which of the following best approximates the original price, in dollars, of the Glenview Street property?
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "x equals 291,666 point 6, with the 6 repeating after the decimal point": leftover tokens: [{"t":"word","v":"with","raw":"with"},{"t":"word","v":"the","raw":"the"},{"t":"num","v":"6"},{"t":"word","v":"repeating","raw":"repeating"},{"t":"word","v":"after","raw":"after"},{"t":"word","v":"the","raw":"the"},{"t":"word","v":"decimal","raw":"decimal"},{"t":"word","v":"point","raw":"point"}]
Corrected stem text <table style="width: 50%;">Townsend Realty Group Investments<thead><tr><th scope="col">Property address</th><th scope="col">Purchase price (dollars)</th><th scope="col">Monthly rental price (dollars)</th></tr></thead><tbody><tr><th scope="row">Clearwater Lane</th><td style="text-align: center;">128,000</td><td style="text-align: center;">950</td></tr><tr><th scope="row">Driftwood Drive</th><td style="text-align: center;">176,000</td><td style="text-align: center;">1,310</td></tr><tr><th scope="row">Edgemont Street</th><td style="text-align: center;">70,000</td><td style="text-align: center;">515</td></tr><tr><th scope="row">Glenview Street</th><td style="text-align: center;">140,000</td><td style="text-align: center;">1,040</td></tr><tr><th scope="row">Hamilton Circle</th><td style="text-align: center;">450,000</td><td style="text-align: center;">3,365</td></tr></tbody><div id="level-access-access-assistant-highlight-container"> </div></table>
<p class="stem_paragraph ">The Townsend Realty Group invested in the five different properties listed in the table above. The table shows the amount, in dollars, the company paid for each property and the corresponding monthly rental price, in dollars, the company charges for the property at each of the five locations. Townsend Realty purchased the Glenview Street property and received a 40% discount off the original price along with an additional 20% off the discounted price for purchasing the property in cash. Which of the following best approximates the original price, in dollars, of the Glenview Street property?</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2544 · Question bank · math · Algebra · type: grid_inno answer key
Currently stored (rendered)
c ( x ) = m x + 500 c(x) = m x + 500 c ( x ) = m x + 500
A company’s total cost c ( x ) c(x) c ( x ) , in dollars, to produce x x x shirts is given by the function above, where m m m is a constant and x > 0 x > 0 x > 0 . The total cost to produce 100 shirts is $800. What is the total cost, in dollars, to produce 1000 shirts? (Disregard the $ sign when gridding your answer.)
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo><mo>=</mo><mi>m</mi><mi>x</mi><mo>+</mo><mn>500</mn></mrow><annotation encoding="application/x-tex">c(x) = m x + 500</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">c</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">m</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">500</span></span></span></span></span></span>
</p>
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<p class="stem_paragraph ">A company’s total cost <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">c(x)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">c</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span></span></span></span></span></span>, in dollars, to produce <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> shirts is given by the function above, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>m</mi></mrow><annotation encoding="application/x-tex">m</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">m</span></span></span></span> is a constant and <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>></mo><mn>0</mn></mrow><annotation encoding="application/x-tex">x > 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.5782em;vertical-align:-0.0391em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">></span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span></span></span>. The total cost to produce 100 shirts is $800. What is the total cost, in dollars, to produce 1000 shirts? (Disregard the $ sign when gridding your answer.)</p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2541 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2526 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2521 · Question bank · math · Algebra · type: grid_inno answer key
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The points plotted in the coordinate plane above represent the possible numbers of wallflowers and cornflowers that someone can buy at the Garden Store in order to spend exactly $24.00 total on the two types of flowers. The price of each wallflower is the same and the price of each cornflower is the same. What is the price, in dollars, of 1 cornflower?
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Corrected stem text <p><img 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" alt="The figure presents a scatterplot titled “Number of Cornflowers and Wallflowers at Garden Store.” The horizontal axis is labeled “Number of cornflowers,” and the numbers 0 through 20, in increments of 2, are indicated. The vertical axis is labeled “Number of wallflowers,” and the numbers 0 through 20, in increments of 2, are indicated. There are 5 data points on the graph. The data represented by the points are as follows.
Data point 1. Number of cornflowers, 0. Number of wallflowers, 12.
Data point 2. Number of cornflowers, 4. Number of wallflowers, 9.
Data point 3. Number of cornflowers, 8. Number of wallflowers, 6.
Data point 4. Number of cornflowers, 12. Number of wallflowers, 3.
Data point 5. Number of cornflowers, 16. Number of wallflowers, 0.
" /></p><p class="stem_paragraph ">The points plotted in the coordinate plane above represent the possible numbers of wallflowers and cornflowers that someone can buy at the Garden Store in order to spend exactly $24.00 total on the two types of flowers. The price of each wallflower is the same and the price of each cornflower is the same. What is the price, in dollars, of 1 cornflower?</p><p></p> Choices (leave blank for a grid-in question) A
B
C
D
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Question #2519 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2512 · Question bank · math · Algebra · type: mcq
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Question #2487 · Question bank · math · Algebra · type: mcq
Currently stored (rendered)
According to data provided by the US Department of Energy, the average price per gallon of regular gasoline in the United States from September 1, 2014, to December 1, 2014, is modeled by the function F F F defined below, where F ( x ) F(x) F ( x ) is the average price per gallon x x x months after September 1.
The constant 2.74 in this function estimates which of the following?
(A) The average monthly decrease in the price per gallon
(B) The difference in the average price per gallon from September 1, 2014, to December 1, 2014
(C) The average price per gallon on September 1, 2014
(D) The average price per gallon on December 1, 2014
Flag reason: 1 math-img alt-text failed MathSpeak conversion: "": empty alt text
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<p class="passage_para ">According to data provided by the US Department of Energy, the average price per gallon of regular gasoline in the United States from September 1, 2014, to December 1, 2014, is modeled by the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi></mrow><annotation encoding="application/x-tex">F</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span> defined below, where <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi><mo stretchy="false">(</mo><mi>x</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">F(x)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span><span class="mopen">(</span><span class="mord mathnormal">x</span><span class="mclose">)</span></span></span></span></span></span> is the average price per gallon <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> months after September 1.</p>
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<p class="standalone_statement style:1 "><span class="math_expression "><span class="math-container"><img align="middle" role="math" class="math-img" src="data:image/png;base64,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" alt="" /></span></span></p>
</div>
<p class="stem_paragraph ">The constant 2.74 in this function estimates which of the following?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #2474 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2470 · Question bank · math · Algebra · type: mcq
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Question #2454 · Question bank · math · Algebra · type: grid_inno answer key
Currently stored (rendered) In the x y xy x y -plane, line k k k intersects the y y y -axis at the point ( 0 , − 6 ) \left(0, -6\right) ( 0 , − 6 ) and passes through the point ( 2 , 2 ) \left(2, 2\right) ( 2 , 2 ) . If the point ( 20 , w ) \left(20, w\right) ( 20 , w ) lies on line k k k , what is the value of w w w ?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p class="stem_paragraph ">In the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane, line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span> intersects the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-axis at the point <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mo>−</mo><mn>6</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0, -6\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">6</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span></span> and passes through the point <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>2</mn><mo separator="true">,</mo><mn>2</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(2, 2\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">2</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">2</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span></span>.<span class="formatted_line_break delivery_mode:Both "></span> If the point <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>20</mn><mo separator="true">,</mo><mi>w</mi><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(20, w\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">20</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0269em;">w</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span></span> lies on line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span>, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>w</mi></mrow><annotation encoding="application/x-tex">w</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0269em;">w</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #2448 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2404 · Question bank · math · Algebra · type: grid_inno answer key
Currently stored (rendered) According to a model, the head width, in millimeters, of a worker bumblebee can be estimated by adding 0.6 to four times the body weight of the bee, in grams. According to the model, what would be the head width, in millimeters, of a worker bumblebee that has a body weight of 0.5 grams?
Flag reason: ibn SPR item has no machine-readable answer key in source data
Corrected stem text <p class="stem_paragraph ">According to a model, the head width, in millimeters, of a worker bumblebee can be estimated by adding 0.6 to four times the body weight of the bee, in grams. According to the model, what would be the head width, in millimeters, of a worker bumblebee that has a body weight of 0.5 grams?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) No source page on record.
Question #2386 · Question bank · math · Algebra · type: mcq
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Question #2385 · Question bank · math · Algebra · type: grid_inno answer key
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Question #2350 · Question bank · math · Problem-Solving and Data Analysis · type: grid_inno answer key
Source PDF page (reference) Question #2094 · Question bank · math · Advanced Math · type: grid_inno answer key
Source PDF page (reference) Question #2058 · Question bank · math · Advanced Math · type: mcq
Source PDF page (reference) Question #2041 · Question bank · math · Advanced Math · type: mcq
Source PDF page (reference) Question #2005 · Question bank · math · Advanced Math · type: mcq
Source PDF page (reference) Question #1985 · Question bank · math · Advanced Math · type: grid_inno answer key
Source PDF page (reference) Question #1934 · Question bank · math · Geometry and Trigonometry · type: grid_inno answer key
Source PDF page (reference) Question #1909 · Question bank · math · Geometry and Trigonometry · type: grid_in
Source PDF page (reference) Question #1819 · Question bank · math · Algebra · type: mcq
Source PDF page (reference) Question #1717 · Question bank · math · Algebra · type: grid_inno answer key
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Source PDF page (reference) Question #1560 · Question bank · math · Algebra · type: grid_inno answer key
Source PDF page (reference) Question #957 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #956 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #954 · Full test · math · type: mcqBank-match candidate available
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Source PDF page (reference) Question #949 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #948 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) For the polynomial function f , the graph of xy-plane passes through the points , and ^4 0 , h. Which of the following must be a factor of fx^ h?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) For the function f f f , the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) in the xy -plane has a slope of 3 3 3 and passes through the point ( 0 , − 8 ) \left(0 , - 8\right) ( 0 , − 8 ) . Which equation defines f f f ?
(A) f ( x ) = 3 x f \left(x\right) = 3 x f ( x ) = 3 x
(B) f ( x ) = 3 x − 8 f \left(x\right) = 3 x - 8 f ( x ) = 3 x − 8
(C) f ( x ) = 3 x + 5 f \left(x\right) = 3 x + 5 f ( x ) = 3 x + 5
(D) f ( x ) = 3 x + 11 f \left(x\right) = 3 x + 11 f ( x ) = 3 x + 11
Suggested correct answer: B mismatches stored answer "C" -- double check
Verified stem text <p style="text-align: left;">For the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>, the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <em>xy</em>-plane has a slope of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3</mn></mrow><annotation encoding="application/x-tex">3</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">3</span></span></span></span> and passes through the point <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mo>−</mo><mn>8</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0 , - 8\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">8</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. Which equation defines <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #946 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #944 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Line k is defined by y = 6x + 4. Line j is parallel to line k in the xy-plane and passes through the point ^0 5 , h. Which equation defines line j?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.67; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In the xy -plane, line k k k passes through the points ( 0 , − 5 ) \left(0 , - 5\right) ( 0 , − 5 ) and ( 1 , − 1 ) \left(1 , - 1\right) ( 1 , − 1 ) . Which equation defines line k k k ?
(A) y = − x + 1 4 y = - x + \dfrac{1}{4} y = − x + 4 1
(B) y = 1 4 x − 5 y = \dfrac{1}{4} x - 5 y = 4 1 x − 5
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: left;">In the <em>xy</em>-plane, line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span> passes through the points <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mo>−</mo><mn>5</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0 , - 5\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">5</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>1</mn><mo separator="true">,</mo><mo>−</mo><mn>1</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(1 , - 1\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">1</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">1</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. Which equation defines line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #942 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #941 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #936 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #933 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #932 · Full test · math · type: grid_in
Currently stored (rendered) For a particular car, the linear function f gives the predicted power, in brake horsepower ^bhp h, for engine speeds between 1,000 revolutions per minute (rpm) and 6,000 rpm. According to this function, the car’s predicted power is 433 bhp at an engine speed of 3,331 rpm and . The , where x is the engine speed, in rpm, and a is a constant. What is the value of a?
Corrected stem text For a particular car, the linear function §IMG§/full-test-images/test-11-math-1-27-inline-0_hi.png§f gives the predicted power, in brake horsepower §IMG§/full-test-images/test-11-math-1-27-inline-1_hi.png§^bhp h, for engine speeds between §IMG§/full-test-images/test-11-math-1-27-inline-2.png§1,000 revolutions per minute (rpm) and §IMG§/full-test-images/test-11-math-1-27-inline-3_hi.png§6,000 rpm. According to this function, the car’s predicted power is §IMG§/full-test-images/test-11-math-1-27-inline-4_hi.png§433 bhp at an engine speed of §IMG§/full-test-images/test-11-math-1-27-inline-5_hi.png§3,331 rpm and . The §IMG§/full-test-images/test-11-math-1-27-inline-6.png§ , where §IMG§/full-test-images/test-11-math-1-27-inline-8_hi.png§x is the engine speed, §IMG§/full-test-images/test-11-math-1-27-inline-7_hi.png§in rpm, and §IMG§/full-test-images/test-11-math-1-27-inline-9_hi.png§a is a constant. What is the value of §IMG§/full-test-images/test-11-math-1-27-inline-10_hi.png§a? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #930 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 2x + 9y = 7 The given equation is one equation in a system of two linear equations. If the system of equations has at least one solution, which of the following equations could be the other equation in the system? I. 3x + 13 5. y = 10 5. II. 3x - 13 5. y = 10 5.
(A) I only
(B) II only
(C) I and II
(D) Neither I nor II
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.72; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) One of the two equations in a linear system is 2 x + 6 y = 10 2 x + 6 y = 10 2 x + 6 y = 10 . The system has no solution. Which of the following could be the other equation in the system?
(B)
x + 3 y = − 20 x + 3 y = -20 x + 3 y = − 20
(C)
6 x − 2 y = 0 6 x - 2 y = 0 6 x − 2 y = 0
(D)
6 x + 2 y = 10 6 x + 2 y = 10 6 x + 2 y = 10
Suggested correct answer: B mismatches stored answer "C" -- double check
Verified stem text <p class="stem_paragraph ">One of the two equations in a linear system is <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn><mi>x</mi><mo>+</mo><mn>6</mn><mi>y</mi><mo>=</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">2 x + 6 y = 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">2</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">6</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></span></span>. The system has no solution. Which of the following could be the other equation in the system?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #928 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #927 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #925 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #924 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #923 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) and umbrellas, y, rented at a park last month and the total spent, in dollars, to rent those beach chairs and umbrellas. Which of the following graphs represents this situation?
(A) C) y 80 70 60 50 40 30 20 10 x O 10 20 30 40 50 60 70 80
(C) B) y 80 70 60 50 40 30 20 10 x O 10 20 30 40 50 60 70 80
(D) y 80 70 60 50 40 30 20 10 x O 10 20 30 40 50 60 70 80
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified) A city’s total expense budget for one year was x x x million dollars. The city budgeted y y y million dollars for departmental expenses and 201 million dollars for all other expenses. Which of the following represents the relationship between x x x and y y y in this context?
(A)
x + y = 201 x + y = 201 x + y = 201
(B)
x − y = 201 x - y = 201 x − y = 201
(C)
2 x − y = 201 2 x - y = 201 2 x − y = 201
(D)
y − x = 201 y - x = 201 y − x = 201
Suggested correct answer: B
Verified stem text <p class="stem_paragraph ">A city’s total expense budget for one year was <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> million dollars. The city budgeted <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span> million dollars for departmental expenses and 201 million dollars for all other expenses. Which of the following represents the relationship between <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span> in this context?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #920 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The scatterplot shows the relationship between x and y. A line of best fit is also shown. Which of the following is closest to the slope of this line of best fit?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.68
Bank-match candidate (unverified) The scatterplot shows the relationship between two variables, x x x and y y y . A line of best fit for the data is also shown. Which of the following is closest to the difference between the y y y -coordinate of the data point with x = 1 x = 1 x = 1 and the y y y -value predicted by the line of best fit at x = 1 x = 1 x = 1 ?
Suggested correct answer: A
Verified stem text <p class="stem_paragraph ">The scatterplot shows the relationship between two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>. A line of best fit for the data is also shown. Which of the following is closest to the difference between the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-coordinate of the data point with <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> and the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-value predicted by the line of best fit at <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> ?</p><div class="standalone_image ">
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" alt="The figure presents a scatterplot in the x y plane. The numbers 0 through 6, in increments of 1, are indicated on the x-axis. The numbers 6 through 12, in increments of 1, are indicated on the y-axis. There are 10 data points in the scatterplot. The data points begin at the point with coordinates 0 comma 12, and trend downward and to the right. The coordinates of the data points are as follows. Note that all values are approximate.
Point 1. 0, comma 12.
Point 2. 0 point 8, comma 11.
Point 3. 1, comma 12.
Point 4. 1 point 5, comma 10 point 3.
Point 5. 2, comma 10.
Point 6. 2 point 2, comma 9 point 2.
Point 7. 3, comma 9.
Point 8. 3 point 5, comma 8.
Point 9. 3 point 8, comma 8 point 3.
Point 10. 4, comma 7.
A line of best fit is also drawn. The line slants downward and to the right, passing through the point with approximate coordinates 1 comma 11, and the point with approximate coordinates 4 comma 7 point 5.
" /></div><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #917 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #916 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #915 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #914 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #911 · Full test · math · type: grid_inno answer key
Source PDF page (reference) Question #910 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #909 · Full test · math · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #908 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) For the linear function f , the graph of y = fx^ h in the xy-plane has a slope of 7 and passes through the point ^0 5 , h. Which equation defines f ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.81; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) For the function f f f , the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) in the xy -plane has a slope of 3 3 3 and passes through the point ( 0 , − 8 ) \left(0 , - 8\right) ( 0 , − 8 ) . Which equation defines f f f ?
(A) f ( x ) = 3 x f \left(x\right) = 3 x f ( x ) = 3 x
(B) f ( x ) = 3 x − 8 f \left(x\right) = 3 x - 8 f ( x ) = 3 x − 8
(C) f ( x ) = 3 x + 5 f \left(x\right) = 3 x + 5 f ( x ) = 3 x + 5
(D) f ( x ) = 3 x + 11 f \left(x\right) = 3 x + 11 f ( x ) = 3 x + 11
Suggested correct answer: B mismatches stored answer "C" -- double check
Verified stem text <p style="text-align: left;">For the function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>, the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <em>xy</em>-plane has a slope of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3</mn></mrow><annotation encoding="application/x-tex">3</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">3</span></span></span></span> and passes through the point <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mo>−</mo><mn>8</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0 , - 8\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">8</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. Which equation defines <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #907 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #906 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #905 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Modularity of mind is the notion that the mind is at least partly composed of innate neural structures (modules) that perform fast, necessary tasks. • 1983: cognitive scientist Jerry A. Fodor hypothesized that low-level cognitive systems (e.g., perception, language) are modular. • In Fodorian modularity, high-level systems (e.g., reasoning) are not modular. • 2003: cognitive scientist Peter Carruthers proposed the massive modularity hypothesis (MMH). • MMH expands modularity to include all cognitive systems. The student wants to compare Fodor’s hypothesis with Carruthers’s. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) In considering some but not all cognitive systems modular, Fodorian modularity is not as expansive in its definition of modularity as MMH is.
(B) Following Fodor’s 1983 hypothesis, Carruthers proposed that modularity of mind includes all cognitive systems.
(C) The hypotheses of Fodor and Carruthers differ in whether they consider low-level cognitive systems, such as perception and language, modular.
(D) In 2003, Carruthers proposed the massive modularity hypothesis, disagreeing with Fodor’s earlier hypothesis that the mind is composed of innate neural structures.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Planetary scientists classify asteroids based on their composition.
C-type asteroids are composed primarily of carbon.
They account for roughly 75 percent of known asteroids.
S-type asteroids are primarily made up of silicate minerals.
They account for roughly 17 percent of known asteroids.
The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Planetary scientists classify asteroids into types, two of which are the C-type and the S-type.
(B) Planetary scientists consider an asteroid’s composition (such as whether the asteroid is composed mainly of silicate minerals or carbon) when classifying it.
(C) Roughly 17 percent of known asteroids are classified as S-type asteroids; another percentage is classified as C-type asteroids.
(D) C-type asteroids are mainly composed of carbon, whereas S-type asteroids are primarily made up of silicate minerals.
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Planetary scientists classify asteroids based on their composition.</li>
<li>C-type asteroids are composed primarily of carbon.</li>
<li>They account for roughly 75 percent of known asteroids.</li>
<li>S-type asteroids are primarily made up of silicate minerals.</li>
<li>They account for roughly 17 percent of known asteroids.</li>
</ul>
<p>The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #904 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Pedestrian malls are outdoor streets in a city or town where vehicle traffic is prohibited. • Many pedestrian malls were built in the 19th and 20th centuries in Europe and Asia. • Qianmen Dajie is a famous pedestrian mall in Beijing. • It has existed since the Ming dynasty (1368–1644 CE). • Rue Mouffetard is a famous pedestrian mall in Paris. • It has existed since the mid-Roman Empire (117–235 CE). The student wants to emphasize a similarity between the ages of the malls. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The Qianmen Dajie pedestrian mall has roots as far back as the Ming dynasty; likewise, Rue Mouffetard has existed for centuries.
(B) Both Qianmen Dajie and Rue Mouffetard are famous pedestrian malls, the former in Beijing and the latter in Paris.
(C) Qianmen Dajie and Rue Mouffetard are pedestrian malls, outdoor streets closed to vehicle traffic.
(D) Qianmen Dajie and Rue Mouffetard are examples of pedestrian malls, which proliferated in Europe in the 19th and 20th centuries.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.
It was the first private turnpike in the United States.
It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.
It was sixty-two miles long.
The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The sixty-two-mile-long Philadelphia and Lancaster Turnpike connected the Pennsylvania cities of Philadelphia and Lancaster.
(B) The Philadelphia and Lancaster Turnpike was the first private turnpike in the United States.
(C) The Philadelphia and Lancaster Turnpike, which connected two Pennsylvania cities, was built between 1792 and 1794.
(D) A historic Pennsylvania road, the Philadelphia and Lancaster Turnpike was completed in 1794.
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.</li>
<li>It was the first private turnpike in the United States.</li>
<li>It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.</li>
<li>It was sixty-two miles long.</li>
</ul>
<p>The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #902 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In Annie Dillard’s Pilgrim at Tinker Creek—where, early on, the author marvels at a single goldfish’s delicate fins but later winces when imagining a horde of goldfish laying and eating their own eggs—Dillard struggles to reconcile the complicated juxtapositions of the natural world. _______ nature’s mesmerizing intricacy and pitiless harshness prove inextricably linked for Dillard, like “two branches of the same creek.” Which choice completes the text with the most logical transition?
(A) To that end,
(B) Ultimately,
(C) Moreover,
(D) Hence,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.42
Bank-match candidate (unverified) The chemical trimethylamine N-oxide not only gives fish their fishy smell but also protects them from crushing hydrostatic pressure in deep waters. Trimethylamine N-oxide strengthens the bonds between water molecules in a fish’s body. ______ blank these water molecules maintain their linked structure at extreme depths, thus preventing pressure-related damage.
Which choice completes the text with the most logical transition?
Suggested correct answer: B
Verified stem text <p>The chemical trimethylamine N-oxide not only gives fish their fishy smell but also protects them from crushing hydrostatic pressure in deep waters. Trimethylamine N-oxide strengthens the bonds between water molecules in a fish’s body. <span>______</span><span class="sr-only">blank</span> these water molecules maintain their linked structure at extreme depths, thus preventing pressure-related damage.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #900 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While studying jorō spiders, a large species originally from East Asia, University of Georgia researchers wondered if the spiders’ rapid spread throughout the southeastern US was a result of aggressive behavior. _______ they discovered that jorō spiders are gentle giants who react to even minor disturbances by “freezing” in place for an hour or more. Which choice completes the text with the most logical transition?
(A) Therefore,
(B) Instead,
(C) For example,
(D) In other words,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified) Most of the planets that have been discovered outside our solar system orbit G-type stars, like our Sun. In 2014, ______ blank researchers identified a planet orbiting KELT-9, a B-type star more than twice as massive and nearly twice as hot as the Sun. Called KELT-9b, it is one of the hottest planets ever discovered.
Which choice completes the text with the most logical transition?
Suggested correct answer: B
Verified stem text <p>Most of the planets that have been discovered outside our solar system orbit G-type stars, like our Sun. In 2014, <span>______</span><span class="sr-only">blank</span> researchers identified a planet orbiting KELT-9, a B-type star more than twice as massive and nearly twice as hot as the Sun. Called KELT-9b, it is one of the hottest planets ever discovered.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #899 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The traditional process of Turkish paper marbling (ebru) generally proceeds like this: First, the artisan fills a shallow tray with a water bath solution. Next, the artisan adds inks or paints to the solution, which can then be manipulated into intricate designs. _______ the artisan slips paper in and out of the liquid, transferring the design onto the paper. Which choice completes the text with the most logical transition?
(A) Actually,
(B) Therefore,
(C) Nevertheless,
(D) Finally,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) To explore how blinking affects social interactions, Dutch researchers observed interactions between human speakers and “listeners” (animated human faces on a screen). The researchers found that when the listeners blinked slowly, the speakers tended to talk for less time. ______ blank quicker blinks were associated with longer talking times.
Which choice completes the text with the most logical transition?
Suggested correct answer: D
Verified stem text <p>To explore how blinking affects social interactions, Dutch researchers observed interactions between human speakers and “listeners” (animated human faces on a screen). The researchers found that when the listeners blinked slowly, the speakers tended to talk for less time. <span>______</span><span class="sr-only">blank</span> quicker blinks were associated with longer talking times.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #897 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) 25 Recordings of electrical activity in the brain, _______ increased activity in brain areas associated with suppressing motor functions. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) electrograms show that while responding to hypothetical match scenarios, the most highly skilled soccer players have
(B) the most highly skilled soccer players responding to hypothetical match scenarios have electrograms that show
(C) responses to hypothetical match scenarios show that the most highly skilled soccer players have electrograms with
(D) hypothetical match scenario responses show that the most highly skilled soccer players captured in electrograms have
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Far from being modern inventions, ______ blank more than 5,000 years ago.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) Sumerians in ancient Mesopotamia used drinking straws
(B) drinking straws were used by Sumerians in ancient Mesopotamia
(C) the use of drinking straws by Sumerians in ancient Mesopotamia happened
(D) ancient Mesopotamia was home to Sumerians who used drinking straws
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p>Far from being modern inventions, <span>______</span><span class="sr-only">blank</span> more than 5,000 years ago.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #893 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #892 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #891 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #888 · Full test · rw · type: mcqno answer key
Currently stored (rendered) In Diné (Navajo) culture, ikaah (sandpaintings) are created and then erased as part of sacred healing ceremonies lasting no more than a few days, but Diné hataałii (chanter, healer, cultural guide) Fred Stevens developed fixatives to preserve desacralized sandpaintings. While on a US-sponsored cultural ambassadorial trip in Europe and the Americas in the 1960s, Stevens produced several such sandpaintings and gave them to cultural institutions. This may seem in tension with the role of cultural ambassador—how could static objects authentically represent an inherently ephemeral and dynamic practice?—but such a view is itself overly object- focused and neglects how Stevens strove to convey exactly those characteristics of ikaah as a cultural practice. Which quotation from an art historian would most directly support the claim made in the text?
(A) “While Stevens’s ambassadorial sandpaintings are undoubtedly educative for audiences that have little exposure to Diné culture, they should not be confused with authentic ikaah, which cannot be extricated from a practice that is intentionally and necessarily transitory nor condensed into a single persistent object.”
(B) “The most compelling way to reconcile the apparent tension between the temporary and performative nature of ikaah and the persistent and static nature of Stevens’s ambassadorial sandpaintings is to recognize that Stevens was an ambassador not only of Diné culture but of a US art culture that tended to value permanent works over ephemeral ones.”
(C) “Stevens’s ambassadorial sandpaintings are best understood not as self-contained objects but as reminders of the public creations of the sandpaintings, during which Stevens conducted appropriate ikaah rituals and encouraged viewers to closely track his movements and subtle shifts in the sand throughout the process.”
(D) “It is important to recall Stevens’s own actions as a gift-giver—a temporary and performative role—of the sandpaintings, for by taking those actions, Stevens publicly enacted the transmission of knowledge of both traditional ikaah practices and cutting-edge chemistry (in the form of the preservative additives), a hybrid that reflects the dynamism of Diné culture.”
Corrected stem text In Diné (Navajo) culture, ikaah (sandpaintings) are created and then erased as part of sacred healing ceremonies lasting no more than a few days, but Diné hataałii (chanter, healer, cultural guide) Fred Stevens developed fixatives to preserve desacralized sandpaintings. While on a US-sponsored cultural ambassadorial trip in Europe and the Americas in the 1960s, Stevens produced several such sandpaintings and gave them to cultural institutions. This may seem in tension with the role of cultural ambassador—how could static objects authentically represent an inherently ephemeral and dynamic practice?—but such a view is itself overly object- focused and neglects how Stevens strove to convey exactly those characteristics of ikaah as a cultural practice. §IMG§/full-test-images/test-11-rw-2-16-inline-0.png§ Which quotation from an art historian would most directly support the claim made in the text? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #887 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Olms are salamanders that live in underwater caves. Scientists once thought that olms stay in their caves all their lives. However, Raoul Manenti and team claim that olms regularly come to the surface to perform important activities such as finding food. Which finding, if true, would most strongly support the underlined claim?
(A) Researchers determine that olms don’t breed often.
(B) Researchers confirm that olms live in only a few cavesystems.
(C) Researchers discover that earthworms from surface soils are a major part of olms’ diet.
(D) Researchers learn that olms’ brains differ from other salamanders’ brains.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) Given that stars and planets initially form from the same gas and dust in space, some astronomers have posited that host stars (such as the Sun) and their planets (such as those in our solar system) are composed of the same materials, with the planets containing equal or smaller quantities of the materials that make up the host star. This idea is also supported by evidence that rocky planets in our solar system are composed of some of the same materials as the Sun.
Which finding, if true, would most directly weaken the astronomers’ claim?
(A) Most stars are made of hydrogen and helium, but when cooled they are revealed to contain small amounts of iron and silicate.
(B) A nearby host star is observed to contain the same proportion of hydrogen and helium as that of the Sun.
(C) Evidence emerges that the amount of iron in some rocky planets is considerably higher than the amount in their host star.
(D) The method for determining the composition of rocky planets is discovered to be less effective when used to analyze other kinds of planets.
Suggested correct answer: C
Verified stem text <p>Given that stars and planets initially form from the same gas and dust in space, some astronomers have posited that host stars (such as the Sun) and their planets (such as those in our solar system) are composed of the same materials, with the planets containing equal or smaller quantities of the materials that make up the host star. This idea is also supported by evidence that rocky planets in our solar system are composed of some of the same materials as the Sun.</p>
<p>Which finding, if true, would most directly weaken the astronomers’ claim?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #884 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Researchers Kate Howlett and Edgar Turner asked 401 schoolchildren in the United Kingdom to draw and label local wildlife. The researchers suggest that the children may be more aware of mammals than of other animals in their environments. Which choice best describes data from the graph that support the researchers’ conclusion?
(A) There were about as many drawings with an example of an insect as there were with an example of a bird.
(B) The fewest number of drawings contained an example of a bird.
(C) More of the drawings had an example of an insect than an example of a mammal.
(D) More of the drawings had an example of a mammal than either an example of a bird or an example of an insect.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.39
Bank-match candidate (unverified)
7 6 5 4 3 2 1 0 Average number of individuals directly reporting to CEO 1991–1995 1996–2001 2001–2008 Average Number of Individuals Reporting Directly to CEOs Years managers department leaders
For each data category, the following bars are shown:
managers
department leaders
All values are approximate.
The data for the 3 categories are as follows:
1991–1995:
managers: 2
department leaders: 3.2
1996–2001:
managers: 2.5
department leaders: 4
2001–2008:
managers: 3
department leaders: 6.9
Considering a large sample of companies, economics experts Maria Guadalupe, Julie Wulf, and Raghuram Rajan assessed the number of managers and leaders from different departments who reported directly to a chief executive officer (CEO). According to the researchers, the findings suggest that across the years analyzed, there was a growing interest among CEOs in connecting with more departments in their companies.
Which choice best describes data from the graph that support the researchers’ conclusion?
(A) The average numbers of managers and department leaders reporting directly to their CEO didn’t fluctuate from the 1991–1995 period to the 2001–2008 period.
(B) The average number of managers reporting directly to their CEO was highest in the 1996–2001 period.
(C) The average number of department leaders reporting directly to their CEO was greater than the average number of managers reporting directly to their CEO in each of the three periods studied.
(D) The average number of department leaders reporting directly to their CEO rose over the three periods studied.
Suggested correct answer: D
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220.85714285714286)">2</text><line fill="none" stroke="#000000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.9" x1="93.359375" x2="385" y1="243.42857142857144" y2="243.42857142857144"></line><line fill="none" stroke="#000000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.9" x1="87.359375" x2="99.359375" y1="243.42857142857144" y2="243.42857142857144"></line><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="end" transform="translate(81.359375 249.42857142857144)">1</text><line fill="none" stroke="#000000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.9" x1="93.359375" x2="385" y1="272" y2="272"></line><line fill="none" stroke="#000000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.9" x1="87.359375" x2="99.359375" y1="272" y2="272"></line><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="end" transform="translate(81.359375 278)">0</text><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="middle" transform="translate(24 172) rotate(-90)">Average number of individuals </text><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="middle" transform="translate(48 172) rotate(-90)">directly reporting to CEO</text><line fill="none" stroke="#000000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.9" x1="93.359375" x2="93.359375" y1="72" y2="272"></line><rect fill="#B3B3B3" height="57.14285714285714" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="122.5234375" y="214.85714285714286"></rect><rect fill="#333333" height="94.28571428571428" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="151.6875" y="177.71428571428572"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="end" transform="translate(161.6075 291.84) rotate(-40)" x="0" y="0">1991–1995</text><rect fill="#B3B3B3" height="71.42857142857143" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="210.015625" y="200.57142857142856"></rect><rect fill="#333333" height="114.28571428571428" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="239.1796875" y="157.71428571428572"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="end" transform="translate(249.0996875 291.84) rotate(-40)" x="0" y="0">1996–2001</text><rect fill="#B3B3B3" height="85.71428571428571" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="297.5078125" y="186.28571428571428"></rect><rect fill="#333333" height="194.28571428571428" stroke="#000000" stroke-linecap="round" stroke-linejoin="mitre" stroke-width="0.9" width="29.1640625" x="326.671875" y="77.71428571428572"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="end" transform="translate(336.591875 291.84) rotate(-40)" x="0" y="0">2001–2008</text><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="middle" transform="translate(239.1796875 24)">Average Number of Individuals</text><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="middle" transform="translate(239.1796875 48)">Reporting Directly to CEOs</text><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="middle" transform="translate(239.1796875 380.46939453125)">Years</text><rect fill="none" height="71" stroke="#000000" stroke-linejoin="mitre" stroke-width="0.9" width="188.046875" x="113.4765625" y="397.62939453125"></rect><rect fill="#B3B3B3" height="12" stroke="#000000" stroke-linejoin="mitre" stroke-width="0.9" width="12" x="120.4765625" y="409.62939453125"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="top" transform="translate(142.4765625 421.62939453125)"> managers</text><rect fill="#333333" height="12" stroke="#000000" stroke-linejoin="mitre" stroke-width="0.9" width="12" x="120.4765625" y="441.62939453125"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="top" transform="translate(142.4765625 453.62939453125)"> department leaders</text></g></svg><div aria-label="Long description for bar graph titled Average Number of Individuals Reporting Directly to CEOs" class="sr-only" role="region"><ul>
<li>For each data category, the following bars are shown:
<ul>
<li>managers</li>
<li>department leaders</li>
</ul>
</li>
<li>All values are approximate.</li>
<li>The data for the 3 categories are as follows:
<ul>
<li>1991–1995:
<ul>
<li>managers: 2</li>
<li>department leaders: 3.2</li>
</ul>
</li>
<li>1996–2001:
<ul>
<li>managers: 2.5</li>
<li>department leaders: 4</li>
</ul>
</li>
<li>2001–2008:
<ul>
<li>managers: 3</li>
<li>department leaders: 6.9</li>
</ul>
</li>
</ul>
</li>
</ul></div>
<p>Considering a large sample of companies, economics experts Maria Guadalupe, Julie Wulf, and Raghuram Rajan assessed the number of managers and leaders from different departments who reported directly to a chief executive officer (CEO). According to the researchers, the findings suggest that across the years analyzed, there was a growing interest among CEOs in connecting with more departments in their companies.</p>
<p>Which choice best describes data from the graph that support the researchers’ conclusion?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #881 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Built in the 1970s, Raccoon Mountain is a pumped- storage hydropower facility (a “water-battery”) located in the United States along the Tennessee River. When energy demand is low, excess power from the regional electric utility’s nuclear plants is used to pump water (from a lower reservoir filled from the Tennessee River) up a shaft to the summit lake, where the water is stored as gravitational potential energy. When energy demand peaks, the water drains down from the summit lake, spinning turbines and generating upward of 1,700 megawatts of power—enough to power one million homes for twentyhours. Which choice best states the main purpose of the text?
(A) To point out the differences between two methods of energy generation
(B) To explain the basics of how a specific energy technology works
(C) To encourage regional electric utilities to build energy storage facilities
(D) To discuss the benefits of a new energy technology
Corrected stem text Built in the 1970s, Raccoon Mountain is a pumped- storage hydropower facility (a “water-battery”) located in the United States along the Tennessee River. When energy demand is low, excess power from the regional electric utility’s nuclear plants is used to pump water (from a lower reservoir filled from the Tennessee River) up a shaft to the summit lake, where the water is stored as gravitational potential energy. When energy demand peaks, the water drains down from the summit lake, spinning turbines and generating upward of 1,700 megawatts of power—enough to power one million homes for twentyhours. Which choice best states the main purpose of the text? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #880 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) A team of researchers discovered that Matabele ants can identify an infected wound in a member of the colony and then treat the infection by covering the wound with antimicrobial secretions that the ants produce. The team found that the mortality rate for Matabele ants with infected injuries was reduced by 90% with this treatment, and they are hopeful that this discovery could aid in the development of new antibiotics for human use. Which choice best describes the overall structure of the text?
(A) It summarizes research findings on Matabele ants and then identifies an area for further research.
(B) It introduces a study of Matabele ants and then explains the research methods used in the study.
(C) It describes unique properties of Matabele ants and then speculates on how those properties evolved.
(D) It identifies an issue concerning Matabele ants and then proposes a solution to address the issue.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) Many archaeologists assume that large-scale engineering projects in ancient societies required an elite class to plan and direct the necessary labor. However, recent discoveries, such as the excavation of an ancient canal near the Gulf Coast of Alabama, have complicated this picture. Using radiocarbon dating, a team of researchers concluded that the 1.39-kilometer-long canal was most likely constructed between 576 and 650 CE by an Indigenous society that was relatively free of social classes.
Which choice best describes the overall structure of the text?
(A) It describes a common view among archaeologists, then discusses a recent finding that challenges that view.
(B) It outlines a method used in some archaeological fieldwork, then explains why an alternative method is superior to it.
(C) It presents contradictory conclusions drawn by archaeologists, then evaluates a study that has apparently resolved that contradiction.
(D) It identifies a gap in scientific research, then presents a strategy used by some archaeologists to remedy that gap.
Suggested correct answer: A
Verified stem text <p>Many archaeologists assume that large-scale engineering projects in ancient societies required an elite class to plan and direct the necessary labor. However, recent discoveries, such as the excavation of an ancient canal near the Gulf Coast of Alabama, have complicated this picture. Using radiocarbon dating, a team of researchers concluded that the 1.39-kilometer-long canal was most likely constructed between 576 and 650 CE by an Indigenous society that was relatively free of social classes.</p>
<p>Which choice best describes the overall structure of the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #878 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In the past, historians who wanted to examine Frederick Douglass’s diary and other personal papers had to visit the Library of Congress in Washington, DC, to view them on microfilm (film containing scaled-down reproductions of documents). But traveling to the library often added time and costs to research projects. Now, by going to the library’s website, researchers can access digitized versions of Douglass’s papers without physically going anywhere. Which choice best describes the function of the underlined portion in the text as a whole?
(A) It gives information about a famous person.
(B) It explains the meaning of a word.
(C) It describes a debate among historians.
(D) It summarizes an unexpected finding.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified) Streams and rivers carry soil and rocks from one location to another. But there is another way for these geological materials to move. Scientists call this process “aeolian transport.” In aeolian transport, winds move small particles of soil or rock over potentially great distances. Geologist Melisa Diaz and her team studied dust in Antarctica to find out if it was moved by aeolian transport. They discovered that the dust matched geological material in Australia. Aeolian transport had carried it from one continent to another, across thousands of miles of open ocean.
Which choice best describes the function of the underlined portion in the text as a whole?
(A) It presents Melisa Diaz’s remarks about difficulties that her team encountered.
(B) It introduces a scientific term that is used in the discussion that follows.
(C) It emphasizes the surprising nature of the findings that are presented.
(D) It explains the difference between two kinds of geological material.
Suggested correct answer: B
Verified stem text <p>Streams and rivers carry soil and rocks from one location to another. But there is another way for these geological materials to move. <span role="region" aria-label="Referenced Content"><u>Scientists call this process “aeolian transport.”</u></span> In aeolian transport, winds move small particles of soil or rock over potentially great distances. Geologist Melisa Diaz and her team studied dust in Antarctica to find out if it was moved by aeolian transport. They discovered that the dust matched geological material in Australia. Aeolian transport had carried it from one continent to another, across thousands of miles of open ocean. </p>
<p>Which choice best describes the function of the underlined portion in the text as a whole?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #876 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #873 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #871 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The meter of a poem is the rhythmic structure or pattern of accents in its lines. • Alliterative meter is structured by a pattern of repeated sounds. • Quantitative meter is structured by a pattern of long and short syllables. • The Old English poem Widsith uses an alliterative meter. • The Sanskrit poem Meghadūta uses a quantitative meter. The student wants to emphasize a difference between the meters of the two poems. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The poem Widsith is written in Old English, but Meghadūta is written in Sanskrit.
(B) Alliterative meter is a pattern of repeated sounds, but quantitative meter is a rhythmic structure or pattern of accents.
(C) The Sanskrit poem Meghadūta uses a quantitative meter, while the meter of the Old English poem Widsith uses a pattern of long and short syllables.
(D) The lines of the poem Meghadūta use a pattern of long and short syllables, whereas Widsith’slines use a pattern of repeated sounds.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.63; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Gaspar Enriquez is an artist.
He specializes in portraits of Mexican Americans.
A portrait is an artistic representation of a person.
Enriquez completed a painting of the sculptor Luis Jimenez in 2003.
He completed a drawing of the writer Rudolfo Anaya in 2016.
The student wants to emphasize a difference between the two portraits. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The portraits, or artistic representations, of Luis Jimenez and Rudolfo Anaya were both completed by Enriquez in the early 2000s.
(B) Enriquez has completed portraits of numerous Mexican Americans, including sculptor Luis Jimenez and writer Rudolfo Anaya.
(C) While both are by Enriquez, the 2003 portrait of Luis Jimenez is a painting, and the 2016 portrait of Rudolfo Anaya is a drawing.
(D) Luis Jimenez was a Mexican American sculptor, and Rudolfo Anaya was a Mexican American writer.
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Gaspar Enriquez is an artist.</li>
<li>He specializes in portraits of Mexican Americans.</li>
<li>A portrait is an artistic representation of a person.</li>
<li>Enriquez completed a painting of the sculptor Luis Jimenez in 2003.</li>
<li>He completed a drawing of the writer Rudolfo Anaya in 2016.</li>
</ul>
<p>The student wants to emphasize a difference between the two portraits. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #870 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • 1914: British explorer Ernest Shackleton and a small crew embarked on an expedition to Antarctica. • 1915: Shackleton’s ship Endurance becamestuck in ice before eventually breaking apart and sinking. • 1916: After more harrowing sea-ice adventures, the entire crew was rescued. • 1959: Historian Alfred Lansing wrote a book called Endurance: Shackleton’s Incredible Voyage. • 2001: Filmmaker George Butler released a documentary called The Endurance: Shackleton’s Legendary Antarctic Expedition. • 2022: The wreckage of Endurance was discovered at the bottom of Antarctica’s Weddell Sea. The student wants to provide a historical overview of the Shackleton expedition. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Leaving in 1914 for Antarctica, Shackleton and his crew underwent many harrowing sea-ice adventures, including losing their ship in 1915, before being rescued in 1916.
(B) In 1914, the Shackleton expedition sailed to Antarctica, where, in 1916, they rescued the crew of a ship that had sunk, Endurance (the wreckage of which was discovered in 2022).
(C) Shackleton’s expedition has inspired a 1959 book, a 2001 film, and a 2022 discovery.
(D) Alfred Lansing wrote about the history of Shackleton’s 1914–16 expedition in the book Endurance: Shackleton’s Incredible Voyage (1959); years later, in 2001, George Butler released a documentary about the expedition.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.51
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Severo Ochoa discovered the enzyme PNPase in 1955.
PNPase is involved in both the creation and degradation of mRNA.
Ochoa incorrectly hypothesized that PNPase provides the genetic blueprints for mRNA.
The discovery of PNPase proved critical to deciphering the human genetic code.
Deciphering the genetic code has led to a better understanding of how genetic variations affect human health.
The student wants to emphasize the significance of Ochoa’s discovery. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Ochoa’s 1955 discovery of PNPase proved critical to deciphering the human genetic code, leading to a better understanding of how genetic variations affect human health.
(B) Ochoa first discovered PNPase, an enzyme that he hypothesized contained the genetic blueprints for mRNA, in 1955.
(C) In 1955, Ochoa discovered the PNPase enzyme, which is involved in both the creation and degradation of mRNA.
(D) Though his discovery of PNPase was critical to deciphering the human genetic code, Ochoa incorrectly hypothesized that the enzyme was the source of mRNA’s genetic blueprints.
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Severo Ochoa discovered the enzyme PNPase in 1955.</li>
<li>PNPase is involved in both the creation and degradation of mRNA.</li>
<li>Ochoa incorrectly hypothesized that PNPase provides the genetic blueprints for mRNA.</li>
<li>The discovery of PNPase proved critical to deciphering the human genetic code.</li>
<li>Deciphering the genetic code has led to a better understanding of how genetic variations affect human health.</li>
</ul>
<p>The student wants to emphasize the significance of Ochoa’s discovery. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #869 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • “Organ2 {}^{2} 2 /ASLSP (As Slow as Possible)” is a musical piece by avant-garde composer John Cage. • A specially designed automated organ in St. Burchardi Church in Halberstadt, Germany, began playing the piece in 2001. • It is scheduled to stop playing the piece in 2640. • The performance will last 639 years. • It will be the longest continuous musical performance in history. The student wants to indicate how long John Cage’s musical piece will last. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) John Cage is the composer of the musical piece “Organ2 {}^{2} 2 /ASLSP (As Slow as Possible).”
(B) “Organ2 {}^{2} 2 /ASLSP (As Slow as Possible)” is a musical piece currently being played in St. Burchardi Church in Halberstadt, Germany.
(C) Lasting 639 years, John Cage’s musical piece will be the longest continuous musical performance in history.
(D) An organ in St. Burchardi Church in Halberstadt, Germany, began playing a musical piece by avant-garde composer John Cage.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
From Earth, all the meteors in a meteor shower appear to originate from a single spot in the sky.
This spot is called the meteor shower’s radiant.
The Perseid meteor shower is visible in the northern hemisphere in July and August.
Like many meteor showers, it is named for the location of its radiant.
Its radiant is located within the constellation Perseus.
The student wants to explain the origin of the Perseid meteor shower’s name. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The Perseid meteor shower is named for the constellation Perseus, the location of the meteor shower’s radiant.
(B) A meteor shower’s name may be linked to a single spot in the sky.
(C) The Perseid meteor shower, which has a radiant, is visible in the northern hemisphere in July and August.
(D) From Earth, all the meteors in a meteor shower appear to originate from a radiant, such as the one within Perseus.
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>From Earth, all the meteors in a meteor shower appear to originate from a single spot in the sky.</li>
<li>This spot is called the meteor shower’s radiant.</li>
<li>The Perseid meteor shower is visible in the northern hemisphere in July and August.</li>
<li>Like many meteor showers, it is named for the location of its radiant.</li>
<li>Its radiant is located within the constellation Perseus.</li>
</ul>
<p>The student wants to explain the origin of the Perseid meteor shower’s name. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #865 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #864 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Helical _______ widely understood to confer stability and efficiency in the locomotion of a variety of microscopic organisms—including bacteria, eukaryotic algae, and ciliates—bestows similar advantages, albeit via different propulsive modes, to larger oceanic macroplanktons, such as salps. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) swimming, is
(B) swimming is
(C) swimming has been
(D) swimming,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Eli Eisenberg, a genetics expert at Tel Aviv University in Israel, recently discovered that ______ blank have a special genetic ability called RNA editing that confers evolutionary advantages.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) cephalopods, ocean dwellers that include the squid, the octopus, and the cuttlefish
(B) cephalopods—ocean dwellers—that include the squid, the octopus, and the cuttlefish,
(C) cephalopods, ocean dwellers that include: the squid, the octopus, and the cuttlefish,
(D) cephalopods—ocean dwellers that include the squid, the octopus, and the cuttlefish—
Suggested correct answer: D
Verified stem text <p>Eli Eisenberg, a genetics expert at Tel Aviv University in Israel, recently discovered that <span>______</span><span class="sr-only">blank</span> have a special genetic ability called RNA editing that confers evolutionary advantages.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #858 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #857 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Like many other genera of wild bees, bumblebees have in recent decades experienced population collapse caused by, among other factors, habitat destruction and climate variation. Bumblebees are also one of the most researched bee genera, second only to honeybees. As a result, ecologists have gained much of their insight about wild-bee declines from bumblebees. In a 2021 paper, zoologist Guillaume Ghisbain notes that bumblebees are among the relatively few wild-bee genera that display social behaviors and dietary generalism (ability to obtain nectar and pollen from a diversity of plant species), two traits that are associated with increased resilience to some specific environmental changes. Ghisbain therefore contends that _______ Which choice most logically completes the text?
(A) although bumblebees and many other wild bees have experienced similar population declines in the past, compared with other wild bees, bumblebees are likely at greater risk of being harmed by climate variation than by habitat destruction.
(B) although bumblebees have been more extensively studied than most wild bees, researchers should not use bumblebees to draw conclusions about the decline of other wild bees, even ones with feeding patterns and levels of sociability that are similar to those of bumblebees.
(C) because bumblebees and other bees with generalist diets are less negatively affected by environmental stress than bees with specialized diets are, they are less likely to experience major population changes in the future than bees with specialized diets are.
(D) because the responses of bumblebees and other wild bees to environmental threats are not always comparable, researchers need to exercise caution when extrapolating information about wild-bee population declines from bumblebees.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Scientists studying Mars long thought the history of its crust was relatively simple. One reason for this is that geologic and climate data collected by a spacecraft showed that the crust was largely composed of basalt, likely as a result of intense volcanic activity that brought about a magma ocean, which then cooled to form the planet’s surface. A study led by Valerie Payré focused on additional information—further analysis of data collected by the spacecraft and infrared wavelengths detected from Mars’s surface—that revealed the presence of surprisingly high concentrations of silica in certain regions on Mars. Since a planetary surface that formed in a mostly basaltic environment would be unlikely to contain large amounts of silica, Payré concluded that ______ blank
Which choice most logically completes the text?
(A) the information about silica concentrations collected by the spacecraft is likely more reliable than the silica information gleaned from infrared wavelengths detected from Mars’s surface.
(B) high silica concentrations on Mars likely formed from a different process than that which formed the crusts of other planets.
(C) having a clearer understanding of the composition of Mars’s crust and the processes by which it formed will provide more insight into how Earth’s crust formed.
(D) Mars’s crust likely formed as a result of other major geological events in addition to the cooling of a magma ocean.
Suggested correct answer: D
Verified stem text <p>Scientists studying Mars long thought the history of its crust was relatively simple. One reason for this is that geologic and climate data collected by a spacecraft showed that the crust was largely composed of basalt, likely as a result of intense volcanic activity that brought about a magma ocean, which then cooled to form the planet’s surface. A study led by Valerie Payré focused on additional information—further analysis of data collected by the spacecraft and infrared wavelengths detected from Mars’s surface—that revealed the presence of surprisingly high concentrations of silica in certain regions on Mars. Since a planetary surface that formed in a mostly basaltic environment would be unlikely to contain large amounts of silica, Payré concluded that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #855 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Founded in 1965 and originally established as a cultural extension of the United Farm Workers—a union representing many Mexican American agricultural workers at the time—the theater troupe El Teatro Campesino has achieved recognition as a source of inspiration for subsequent Chicano theater companies and as a contributor to the dramatic arts. In an article about the company, a theater historian posits that a significant stylistic influence on El Teatro’s early performances was the audience-mediated slapstick comedy of carpa theater, vaudeville-style shows popular in Mexico and the US Southwest in the 1920s and ’30s. Which quotation from the article would best illustrate the theater historian’s claim?
(A) “The company presented actos, short comedy sketches, that often relied on exaggerated physical humor to groups of agricultural workers, whose reactions—enthusiastic cheers of appreciation and, occasionally, loud boos of disapproval—promotedimprovisation.”
(B) “The company was focused on the reality of the present situation and discovered that humor was often found in that reality; consequently, comedy became a tool to convey social critique while entertaining and inspiring audiences.”
(C) “The company relied heavily on satire, humor, and references to contemporary popular culture as well as a make-do aesthetic—often referred to as rasquache—that reflected not only the troupe’s limited financial resources but also its sociopolitical message.”
(D) “The members of the company, which in addition to founder Luis Valdez consisted entirely of nonprofessional actors, traveled into farm fields, where they, with minimal props and costumes, performed comedy in the form of brief humorous vignettes.”
Corrected stem text Founded in 1965 and originally established as a cultural extension of the United Farm Workers—a union representing many Mexican American agricultural workers at the time—the theater troupe El Teatro Campesino has achieved recognition as a source of inspiration for subsequent Chicano theater companies and as a contributor to the dramatic arts. In an article about the company, a theater historian posits that a significant stylistic influence on El Teatro’s early performances was the audience-mediated slapstick comedy of carpa theater, vaudeville-style shows popular in Mexico and the US Southwest in the 1920s and ’30s. Which quotation from the article would best illustrate the theater historian’s claim? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #852 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The following text is from Mick Herron’s 2023 novel The Secret Hours. The narrator is describing members of a government committee. Finally, and adding much-needed gravitas, was Sir Winston Day, whose features seemed moulded to adorn a bust, or possibly a stamp, and whose forehead was so evidently bulging with grey matter that it would have been impertinent to inquire too closely into the actual achievements his half century of public service had produced. His recently published memoirs possibly cast light on this enigma, but given that such details were not provided until after the thirty-page mark, they might as well have remained state secrets. ©2023 by Mick Herron Based on the text, which choice best describes Sir Winston Day?
(A) He has the appearance of a distinguished figure, but it is uncertain whether he has accomplished anything to earn distinction.
(B) He looks like a person worthy of respect, but his memoirs reveal that some of his actions were dishonorable.
(C) He would be a celebrated public figure if his achievements did not have to be kept secret.
(D) He has maintained a modest profile even though he has served the public capably for many years.
Corrected stem text The following text is from Mick Herron’s 2023 novel The Secret Hours. The narrator is describing members of a government committee. Finally, and adding much-needed gravitas, was Sir Winston Day, whose features seemed moulded to adorn a bust, or possibly a stamp, and whose forehead was so evidently bulging with grey matter that it would have been impertinent to inquire too closely into the actual achievements his half century of public service had produced. His recently published memoirs possibly cast light on this enigma, but given that such details were not provided until after the thirty-page mark, they might as well have remained state secrets. ©2023 by Mick Herron Based on the text, which choice best describes Sir Winston Day? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #851 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The following text is from Mark Haber’s 2022 novel Saint Sebastian’s Abyss. The narrator and Schmidt are both art critics. When my first wife admitted to Schmidt over dinner that she didn’t find art, painting in particular, especially compelling, Schmidt winced, set down his fork, and sighed dramatically; he then excused himself, explaining an appointment he’d forgotten about had suddenly and inexplicably been remembered, while making it abundantly clear there was no appointment at all. ©2022 by Mark Haber Based on the text, what is notable about Schmidt’s behavior?
(A) Schmidt is only given to theatrical behavior when in the company of the narrator and his first wife.
(B) Schmidt’s absentmindedness regarding his schedule is uncharacteristic of him.
(C) Schmidt’s departure is occasioned by the resumption of a previous disagreement with the narrator’s first wife about a particular painting.
(D) Schmidt conveys his feelings about one of his dining companions without explicitly stating them.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.42
Bank-match candidate (unverified) The following text is from Herman Melville’s 1854 novel The Lightning-rod Man .
The stranger still stood in the exact middle of the cottage, where he had first planted himself. His singularity impelled a closer scrutiny. A lean, gloomy figure. Hair dark and lank, mattedly streaked over his brow. His sunken pitfalls of eyes were ringed by indigo halos, and played with an innocuous sort of lightning: the gleam without the bolt. The whole man was dripping. He stood in a puddle on the bare oak floor: his strange walking-stick vertically resting at his side.
Which choice best states the function of the underlined sentence in the overall structure of the text?
(A) It elaborates on the previous sentence’s description of the character.
(B) It introduces the setting that is described in the sentences that follow.
(C) It establishes a contrast with the description in the previous sentence.
(D) It sets up the character description presented in the sentences that follow.
Suggested correct answer: D
Verified stem text <p>The following text is from Herman Melville’s 1854 novel <em>The Lightning-rod Man</em>.</p>
<p>The stranger still stood in the exact middle of the cottage, where he had first planted himself. <span role="region" aria-label="Referenced Content"><u>His singularity impelled a closer scrutiny.</u></span> A lean, gloomy figure. Hair dark and lank, mattedly streaked over his brow. His sunken pitfalls of eyes were ringed by indigo halos, and played with an innocuous sort of lightning: the gleam without the bolt. The whole man was dripping. He stood in a puddle on the bare oak floor: his strange walking-stick vertically resting at his side.</p>
<p>Which choice best states the function of the underlined sentence in the overall structure of the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #849 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The average age at which people in the United States start businesses is 35. Economist Andrés Hincapié studied why young adults are relatively less likely to start businesses and whether there are ways to increase entrepreneurship in early adulthood. Hincapié found that one impediment is lack of knowledge about the practical details of how businesses are started; he further found that simply providing young adults with good informational resources on the topic significantly alleviates this problem. Based on the text, what would Hincapié most likely say is a promising way to increase entrepreneurship in early adulthood?
(A) Creating social networks of young adults who are interested in starting a business
(B) Encouraging young adults to brainstorm business ideas
(C) Providing young adults with practical information about how to start a business
(D) Giving young adults training opportunities at a variety of businesses
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.43
Bank-match candidate (unverified) Text 1
Public policy researcher Anthony Fowler studied the history of elections in Australia, a country that requires citizens to vote. Fowler argues that requiring citizens to vote leads to a significant increase in voters who would otherwise not have the time or motivation to vote. Thus, election results in countries that require citizens to vote better reflect the preferences of the country as a whole.
Text 2
Governments in democratic countries function better when more people vote. However, forcing people to vote may have negative consequences. Shane P. Singh and Jason Roy studied what happens when a country requires its citizens to vote. They found that when people feel forced to vote, they tend to spend less time looking for information about their choices when voting. As a result, votes from these voters may not reflect their actual preferences.
Based on the texts, how would Singh and Roy (Text 2) most likely respond to the research discussed in Text 1?
(A) Only countries of a certain population size should implement mandatory voting.
(B) People who are forced to vote are likely to become politically engaged in other ways, such as volunteering or running for office.
(C) Requiring people to vote does not necessarily lead to election outcomes that better represent the preferences of the country as a whole.
(D) Countries that require voting must also make the process of voting easier for their citizens.
Suggested correct answer: C
Verified stem text <p><span role="heading"><strong>Text 1</strong></span></p>
<p>Public policy researcher Anthony Fowler studied the history of elections in Australia, a country that requires citizens to vote. Fowler argues that requiring citizens to vote leads to a significant increase in voters who would otherwise not have the time or motivation to vote. Thus, election results in countries that require citizens to vote better reflect the preferences of the country as a whole. </p>
<p> </p>
<p><span role="heading"><strong>Text 2</strong></span></p>
<p>Governments in democratic countries function better when more people vote. However, forcing people to vote may have negative consequences. Shane P. Singh and Jason Roy studied what happens when a country requires its citizens to vote. They found that when people feel forced to vote, they tend to spend less time looking for information about their choices when voting. As a result, votes from these voters may not reflect their actual preferences.</p>
<p>Based on the texts, how would Singh and Roy (Text 2) most likely respond to the research discussed in Text 1?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #847 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Curious about how people visually perceive objects in their dreams, Stephen LaBerge and team recruited lucid dreamers—people aware that they’re dreaming as it’s happening—for a research study. These participants were reliably able to signal when they had entered a dream state; the team then observed participants’ eye movements as they slept. The smoothness with which participants’ eyes tracked objects in their dreams closely matched how sighted people who are awake visually track objects around them, suggesting to the team that the brain perceives dream objects as the product of something other than pure imagination. Which choice best states the function of the underlined portion in the text as a whole?
(A) To offer key evidence that undermines LaBerge and team’s initial hypothesis
(B) To show the unexpected result that led LaBerge and team to change the focus of their study
(C) To illustrate an important real-world implication of LaBerge and team’s main finding
(D) To identify a comparable circumstance that helps justify LaBerge and team’s conclusion
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Text 1
In a study of insect behavior, Samadi Galpayage and colleagues presented bumblebees with small wooden balls and observed many of the bees clinging to, rolling, and dragging the objects. The researchers provided no external rewards (such as food) to encourage these interactions. The bees simply appeared to be playing—and for no other reason than because they were having fun .
Text 2
Insects do not have cortexes or other brain areas associated with emotions in humans. Still, Galpayage and her team have shown that bumblebees may engage in play, possibly experiencing some kind of positive emotional state. Other studies have suggested that bees experience negative emotional states (for example, stress), but as Galpayage and her team have acknowledged, emotions in insects, if they do indeed exist, are likely very rudimentary.
Based on the texts, how would the author of Text 2 most likely respond to the underlined portion of Text 1?
(A) By objecting that the bees were actually experiencing a negative feeling akin to stress rather than a positive feeling
(B) By arguing that some insects other than bumblebees may be capable of experiencing complex emotional states
(C) By pointing out that even humans sometimes struggle to have fun while engaging in play
(D) By noting that if the bees were truly playing, any positive feelings they may have experienced were probably quite basic
Suggested correct answer: D
Verified stem text <p><strong>Text 1</strong></p>
<p>In a study of insect behavior, Samadi Galpayage and colleagues presented bumblebees with small wooden balls and observed many of the bees clinging to, rolling, and dragging the objects. The researchers provided no external rewards (such as food) to encourage these interactions. <u>The bees simply appeared to be playing—and for no other reason than because they were having fun</u>.</p>
<p><strong>Text 2</strong></p>
<p>Insects do not have cortexes or other brain areas associated with emotions in humans. Still, Galpayage and her team have shown that bumblebees may engage in play, possibly experiencing some kind of positive emotional state. Other studies have suggested that bees experience negative emotional states (for example, stress), but as Galpayage and her team have acknowledged, emotions in insects, if they do indeed exist, are likely very rudimentary.</p>
<p>Based on the texts, how would the author of Text 2 most likely respond to the underlined portion of Text 1?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #844 · Full test · rw · type: mcq
Source PDF page (reference) Question #843 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #841 · Full test · rw · type: mcq
Source PDF page (reference) Question #840 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #838 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Two data sets of 23 integers each are summarized in the histograms shown. For each of the histograms, the first interval represents the frequency of integers greater than or equal to 10, but less than 20. The second interval represents the frequency of integers greater than or equal to 20, but less than 30, and so on. What is the smallest possible difference between the mean of data set A and the mean of data set B?
(A) 0
(B) 1
(C) 10
(D) 23
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.71
Bank-match candidate (unverified)
Data Set A:
The horizontal axis is labeled Integer. It ranges from 10 to 60 and is divided into 5 equal intervals.
The vertical axis is labeled Frequency. It ranges from 0 to 12 in increments of 1, with values marked every 2 grid lines.
The histogram has a skewed right shape.
The histogram has 4 bins.
The Frequency data for the 4 bins are as follows:
20 to 30: 3
30 to 40: 4
40 to 50: 7
50 to 60: 9
Data Set B:
The horizontal axis is labeled Integer. It ranges from 10 to 60 and is divided into 5 equal intervals.
The vertical axis is labeled Frequency. It ranges from 0 to 12 in increments of 1, with values marked every 2 grid lines.
The histogram has a skewed right shape.
The histogram has 4 bins.
The Frequency data for the 4 bins are as follows:
10 to 20: 3
20 to 30: 4
30 to 40: 7
40 to 50: 9
Two data sets of 23 23 23 integers each are summarized in the histograms shown. For each of the histograms, the first interval represents the frequency of integers greater than or equal to 10 10 10 , but less than 20 20 20 . The second interval represents the frequency of integers greater than or equal to 20 20 20 , but less than 30 30 30 , and so on. What is the smallest possible difference between the mean of data set A and the mean of data set B?
Suggested correct answer: B
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d="M396.994,201.127a8.128,8.128,0,0,1,1.143-4.438,3.549,3.549,0,0,1,6.173-.01,9.235,9.235,0,0,1-.01,8.886,3.522,3.522,0,0,1-6.153-.01A8.081,8.081,0,0,1,396.994,201.127Zm1.706-.02a10.061,10.061,0,0,0,.677,3.925q.679,1.6,1.745,1.6,1.24,0,1.928-1.609a10.238,10.238,0,0,0,.688-4.011,9.566,9.566,0,0,0-.678-3.847q-.678-1.54-1.744-1.541-1.182,0-1.9,1.57A9.4,9.4,0,0,0,398.7,201.107Z" fill="#231f20"></path></g></svg><div role="region" aria-label="Long description for 2 histograms titled Data Set A and Data Set B" class="sr-only"><ul>
<li>Data Set A:
<ul>
<li>The horizontal axis is labeled Integer. It ranges from 10 to 60 and is divided into 5 equal intervals.</li>
<li>The vertical axis is labeled Frequency. It ranges from 0 to 12 in increments of 1, with values marked every 2 grid lines.</li>
<li>The histogram has a skewed right shape.</li>
<li>The histogram has 4 bins.</li>
<li>The Frequency data for the 4 bins are as follows:
<ul>
<li>20 to 30: 3</li>
<li>30 to 40: 4</li>
<li>40 to 50: 7</li>
<li>50 to 60: 9</li>
</ul>
</li>
</ul>
</li>
<li>Data Set B:
<ul>
<li>The horizontal axis is labeled Integer. It ranges from 10 to 60 and is divided into 5 equal intervals.</li>
<li>The vertical axis is labeled Frequency. It ranges from 0 to 12 in increments of 1, with values marked every 2 grid lines.</li>
<li>The histogram has a skewed right shape.</li>
<li>The histogram has 4 bins.</li>
<li>The Frequency data for the 4 bins are as follows:
<ul>
<li>10 to 20: 3</li>
<li>20 to 30: 4</li>
<li>30 to 40: 7</li>
<li>40 to 50: 9</li>
</ul>
</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">Two data sets of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>23</mn></mrow><annotation encoding="application/x-tex">23</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">23</span></span></span></span> integers each are summarized in the histograms shown. For each of the histograms, the first interval represents the frequency of integers greater than or equal to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>10</mn></mrow><annotation encoding="application/x-tex">10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span>, but less than <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>20</mn></mrow><annotation encoding="application/x-tex">20</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">20</span></span></span></span>. The second interval represents the frequency of integers greater than or equal to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>20</mn></mrow><annotation encoding="application/x-tex">20</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">20</span></span></span></span>, but less than <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>30</mn></mrow><annotation encoding="application/x-tex">30</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">30</span></span></span></span>, and so on. What is the smallest possible difference between the mean of data set A and the mean of data set B?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #837 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #834 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #829 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #828 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The graph shows the relationship between the number of shares of stock from Company A, x, and the number of shares of stock from Company B, y, that Simone can purchase. Which equation could represent this relationship?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.79
Bank-match candidate (unverified)
The line slants down from left to right.
The line passes through the following points:
(0 comma 40)
(60 comma 0)
The graph shows the relationship between the number of shares of stock from Company A, x x x , and the number of shares of stock from Company B, y y y , that Simone can purchase. Which equation could represent this relationship?
(A) y = 8 x + 12 y = 8 x + 12 y = 8 x + 12
(B) 8 x + 12 y = 480 8 x + 12 y = 480 8 x + 12 y = 480
(C) y = 12 x + 8 y = 12 x + 8 y = 12 x + 8
(D) 12 x + 8 y = 480 12 x + 8 y = 480 12 x + 8 y = 480
Suggested correct answer: B
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<div aria-label="Long description for graph of a line" class="sr-only" role="region"><ul>
<li>The line slants down from left to right.</li>
<li>The line passes through the following points:
<ul>
<li>(0 comma 40)</li>
<li>(60 comma 0)</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">The graph shows the relationship between the number of shares of stock from Company A, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span>, and the number of shares of stock from Company B, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>, that Simone can purchase. Which equation could represent this relationship?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #827 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) In right triangleR ST, the sum of the measures of angle R and angle S is 90 degrees. The value of 15 s in(R ) is . What is the value ofc os(S ) ? 4
(A) 15
(B) 4 15
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.77
Bank-match candidate (unverified) In right triangle R S T R S T R S T , the sum of the measures of angle R R R and angle S S S is 90 90 90 degrees. The value of sin ( R ) \sin \left(R\right) sin ( R ) is 15 4 \dfrac{\sqrt{15}}{4} 4 15 . What is the value of cos ( S ) \cos \left(S\right) cos ( S ) ?
(A) 15 15 \dfrac{\sqrt{15}}{15} 15 15
(B) 15 4 \dfrac{\sqrt{15}}{4} 4 15
(C) 4 15 15 \dfrac{4 \sqrt{15}}{15} 15 4 15
Suggested correct answer: B
Verified stem text <p>In right triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi><mi>S</mi><mi>T</mi></mrow><annotation encoding="application/x-tex">R S T</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span><span class="mord mathnormal" style="margin-right:0.0576em;">S</span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span></span></span></span>, the sum of the measures of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>R</mi></mrow><annotation encoding="application/x-tex">R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span></span></span></span> and angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>S</mi></mrow><annotation encoding="application/x-tex">S</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">S</span></span></span></span> is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>90</mn></mrow><annotation encoding="application/x-tex">90</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">90</span></span></span></span> degrees. The value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>sin</mi><mo></mo><mrow><mo fence="true">(</mo><mi>R</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">\sin \left(R\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mop">sin</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal" style="margin-right:0.0077em;">R</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><msqrt><mn>15</mn></msqrt><mn>4</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\dfrac{\sqrt{15}}{4}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:2.2702em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.5842em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">4</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">15</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #826 · Full test · math · type: grid_inBank-match candidate available
Currently stored (rendered) g is defined by , where a is a positive constant. If , what is the value of g(4) ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.63; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The exponential function g g g is defined by g ( x ) = 19 ⋅ a x g \left(x\right) = 19 \cdot a^{x} g ( x ) = 19 ⋅ a x , where a a a is a positive constant. If g ( 3 ) = 2 , 375 g \left(3\right) = 2,375 g ( 3 ) = 2 , 375 , what is the value of g ( 4 ) g \left(4\right) g ( 4 ) ?
Suggested correct answer: 11875 mismatches stored answer "11 875," -- double check
Verified stem text <p>The exponential function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi></mrow><annotation encoding="application/x-tex">g</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>19</mn><mo>⋅</mo><msup><mi>a</mi><mi>x</mi></msup></mrow><annotation encoding="application/x-tex">g \left(x\right) = 19 \cdot a^{x}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">19</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">⋅</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6644em;"></span><span class="mord"><span class="mord mathnormal">a</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6644em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">x</span></span></span></span></span></span></span></span></span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> is a positive constant. If <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi><mrow><mo fence="true">(</mo><mn>3</mn><mo fence="true">)</mo></mrow><mo>=</mo><mn>2</mn><mo separator="true">,</mo><mn>375</mn></mrow><annotation encoding="application/x-tex">g \left(3\right) = 2,375</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">3</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">2</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">375</span></span></span></span>, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>g</mi><mrow><mo fence="true">(</mo><mn>4</mn><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">g \left(4\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">g</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">4</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #823 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #820 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Of 300,000 paper clips, 234,000 are size large. What percentage of the paper clips are size large?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58
Bank-match candidate (unverified) Of 900 , 000 900,000 900 , 000 beads, 828 , 000 828,000 828 , 000 are silver. What percentage of the beads are silver?
Suggested correct answer: D
Verified stem text <p style="text-align: left;">Of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>900</mn><mo separator="true">,</mo><mn>000</mn></mrow><annotation encoding="application/x-tex">900,000</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">900</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">000</span></span></span></span> beads, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>828</mn><mo separator="true">,</mo><mn>000</mn></mrow><annotation encoding="application/x-tex">828,000</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">828</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">000</span></span></span></span> are silver. What percentage of the beads are silver?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #817 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #815 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #814 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The scatterplot shows the relationship between two variables, x and y. A line of best fit is also shown. Which of the following equations best represents the line of best fit shown?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.69
Bank-match candidate (unverified) The scatterplot shows the relationship between two variables, x x x and y y y . A line of best fit for the data is also shown. Which of the following is closest to the difference between the y y y -coordinate of the data point with x = 1 x = 1 x = 1 and the y y y -value predicted by the line of best fit at x = 1 x = 1 x = 1 ?
Suggested correct answer: A
Verified stem text <p class="stem_paragraph ">The scatterplot shows the relationship between two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>. A line of best fit for the data is also shown. Which of the following is closest to the difference between the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-coordinate of the data point with <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> and the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-value predicted by the line of best fit at <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> ?</p><div class="standalone_image ">
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" alt="The figure presents a scatterplot in the x y plane. The numbers 0 through 6, in increments of 1, are indicated on the x-axis. The numbers 6 through 12, in increments of 1, are indicated on the y-axis. There are 10 data points in the scatterplot. The data points begin at the point with coordinates 0 comma 12, and trend downward and to the right. The coordinates of the data points are as follows. Note that all values are approximate.
Point 1. 0, comma 12.
Point 2. 0 point 8, comma 11.
Point 3. 1, comma 12.
Point 4. 1 point 5, comma 10 point 3.
Point 5. 2, comma 10.
Point 6. 2 point 2, comma 9 point 2.
Point 7. 3, comma 9.
Point 8. 3 point 5, comma 8.
Point 9. 3 point 8, comma 8 point 3.
Point 10. 4, comma 7.
A line of best fit is also drawn. The line slants downward and to the right, passing through the point with approximate coordinates 1 comma 11, and the point with approximate coordinates 4 comma 7 point 5.
" /></div><p></p> Choices (leave blank for a grid-in question) A
B
C
D
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Currently stored (rendered) - The graph of a system of linear equations is shown. What is the solution( xy, ) to the system?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59
Bank-match candidate (unverified)
A system of two linear equations is graphed in the x y xy x y -plane below.
Which of the following points is the solution to the system of equations?
(A)
( 3 , 9 ) \left(3, 9\right) ( 3 , 9 )
(B)
( 6 , 15 ) \left(6, 15\right) ( 6 , 15 )
(C)
( 8 , 10 ) \left(8, 10\right) ( 8 , 10 )
(D)
( 12 , 18 ) \left(12, 18\right) ( 12 , 18 )
Suggested correct answer: A
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<p class="passage_para ">A system of two linear equations is graphed in the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane below.</p>
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alt="The figure presents the graph of 2 lines in the x y plane. The numbers negative 4 through 16, in increments of 2, are indicated on the x axis. The numbers negative 4 through 20, in increments of 2, are indicated on the y axis. One line begins above the x axis and to the left of the y axis. It moves upward and to the right, crossing the y axis at 6, and passing through the point with coordinates 3 comma 9 and the point with coordinates 12 comma 18. The other line begins below the x axis and to the left of the y axis. It moves upward and to the right, crossing the y axis at 3, and passing through the point with coordinates 3 comma 9 and the point with coordinates 6 comma 15. The two lines intersect at the point with coordinates 3 comma 9." /></div>
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<p class="stem_paragraph ">Which of the following points is the solution to the system of equations?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #786 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 1 The line graph shows the percent of cars for sale at a used car lot on a given day by model year. For what model year is the percent of cars for sale the smallest?
(A) 2012
(B) 2013
(C) 2014
(D) 2015
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.68
Bank-match candidate (unverified) The line graph shows the percent of cars for sale at a used car lot on a given day by model year.
The line graph:
Begins at 2010, 12%
Remains level to 2011, 12%
Remains level to 2012, 12%
Falls sharply to 2013, 8%
Falls sharply to 2014, 4%
Rises sharply to 2015, 9%
Rises gradually to 2016, 10%
Remains level to 2017, 10%
Rises gradually to 2018, 11%
Remains level to 2019, 11%
For what model year is the percent of cars for sale the smallest?
Suggested correct answer: C
Verified stem text <p style="text-align: left;">The line graph shows the percent of cars for sale at a used car lot on a given day by model year.</p>
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<li>The line graph:<br />
<ul>
<li>Begins at 2010, 12%</li>
<li>Remains level to 2011, 12%</li>
<li>Remains level to 2012, 12%</li>
<li>Falls sharply to 2013, 8%</li>
<li>Falls sharply to 2014, 4%</li>
<li>Rises sharply to 2015, 9%</li>
<li>Rises gradually to 2016, 10%</li>
<li>Remains level to 2017, 10%</li>
<li>Rises gradually to 2018, 11%</li>
<li>Remains level to 2019, 11%</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">For what model year is the percent of cars for sale the smallest?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #785 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • In 1851, German American artist Emanuel Leutze painted Washington Crossing the Delaware. • His huge painting (149 × 255 inches) depicts the first US president crossing a river with soldiers in the Revolutionary War. • In 2019, Cree artist Kent Monkman painted mistikôsiwak (Wooden Boat People): Resurgence of the People. • Monkman’s huge painting (132 × 264 inches) was inspired by Leutze’s. • It portrays Indigenous people in a boat rescuing refugees. The student wants to emphasize a similarity between the two paintings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Monkman, a Cree artist, finished his painting in 2019; Leutze, a German American artist, completed his in 1851.
(B) Although Monkman’s painting was inspired by Leutze’s, the people and actions the two paintings portray are very different.
(C) Leutze’s and Monkman’s paintings are both huge, measuring 149 × 255 inches and 132 × 264 inches, respectively.
(D) Leutze’s painting depicts Revolutionary War soldiers, while Monkman’s depicts Indigenous people and refugees.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
In 1851, German American artist Emanuel Leutze painted Washington Crossing the Delaware .
His huge painting (149 × 255 inches) depicts the first US president crossing a river with soldiers in the Revolutionary War.
In 2019, Cree artist Kent Monkman painted mistikôsiwak (Wooden Boat People): Resurgence of the People .
Monkman’s huge painting (132 × 264 inches) was inspired by Leutze’s.
It portrays Indigenous people in a boat rescuing refugees.
The student wants to emphasize a similarity between the two paintings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Monkman, a Cree artist, finished his painting in 2019; Leutze, a German American artist, completed his in 1851.
(B) Although Monkman’s painting was inspired by Leutze’s, the people and actions the two paintings portray are very different.
(C) Leutze’s and Monkman’s paintings are both huge, measuring 149 × 255 inches and 132 × 264 inches, respectively.
(D) Leutze’s painting depicts Revolutionary War soldiers, while Monkman’s depicts Indigenous people and refugees.
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>In 1851, German American artist Emanuel Leutze painted <em>Washington Crossing the Delaware</em>.</li>
<li>His huge painting (149 × 255 inches) depicts the first US president crossing a river with soldiers in the Revolutionary War.</li>
<li>In 2019, Cree artist Kent Monkman painted <em>mistikôsiwak (Wooden Boat People): Resurgence of the People</em>.</li>
<li>Monkman’s huge painting (132 × 264 inches) was inspired by Leutze’s.</li>
<li>It portrays Indigenous people in a boat rescuing refugees.</li>
</ul>
<p>The student wants to emphasize a similarity between the two paintings. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #784 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Started in 1925, the Scripps National Spelling Bee is a US-based spelling competition. • The words used in the competition have diverse linguistic origins. • In 2008, Sameer Mishra won by correctly spelling the word “guerdon.” • “Guerdon” derives from the Anglo-French word “guerdun.” • In 2009, Kavya Shivashankar won by correctly spelling the word “Laodicean.” • “Laodicean” derives from the ancient Greek word “Laodíkeia.” The student wants to emphasize a difference in the origins of the two words. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) “Guerdon,” the final word of the 2008 Scripps National Spelling Bee, is of Anglo-French origin, while the following year’s final word, “Laodicean,” derives from ancient Greek.
(B) In 2008, Sameer Mishra won the Scripps National Spelling Bee by correctly spelling the word “guerdon”; however, the following year, Kavya Shivashankar won based on spelling the word “Laodicean.”
(C) Kavya Shivashankar won the 2009 Scripps National Spelling Bee by correctly spelling “Laodicean,” which derives from the ancient Greek word “Laodíkeia.”
(D) The Scripps National Spelling Bee uses words from diverse linguistic origins, such as “guerdon” and “Laodicean.”
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Started in 1925, the Scripps National Spelling Bee is a US-based spelling competition.
The words used in the competition have diverse linguistic origins.
In 2008, Sameer Mishra won by correctly spelling the word “guerdon.”
“Guerdon” derives from the Anglo-French word “guerdun.”
In 2009, Kavya Shivashankar won by correctly spelling the word “Laodicean.”
“Laodicean” derives from the ancient Greek word “Laodíkeia. ”
The student wants to emphasize a difference in the origins of the two words. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) “Guerdon,” the final word of the 2008 Scripps National Spelling Bee, is of Anglo-French origin, while the following year’s final word, “Laodicean,” derives from ancient Greek.
(B) In 2008, Sameer Mishra won the Scripps National Spelling Bee by correctly spelling the word “guerdon”; however, the following year, Kavya Shivashankar won based on spelling the word “Laodicean.”
(C) Kavya Shivashankar won the 2009 Scripps National Spelling Bee by correctly spelling “Laodicean,” which derives from the ancient Greek word “Laodíkeia. ”
(D) The Scripps National Spelling Bee uses words from diverse linguistic origins, such as “guerdon” and “Laodicean.”
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Started in 1925, the Scripps National Spelling Bee is a US-based spelling competition.</li>
<li>The words used in the competition have diverse linguistic origins.</li>
<li>In 2008, Sameer Mishra won by correctly spelling the word “guerdon.”</li>
<li>“Guerdon” derives from the Anglo-French word “guerdun.”</li>
<li>In 2009, Kavya Shivashankar won by correctly spelling the word “Laodicean.”</li>
<li>“Laodicean” derives from the ancient Greek word “<span>Laodíkeia.</span>”</li>
</ul>
<p>The student wants to emphasize a difference in the origins of the two words. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #783 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Shaun Tan is an Australian author. • In 2008, he published Tales from Outer Suburbia, a book of fifteen short stories. • The stories describe surreal events occurring in otherwise ordinary suburban neighborhoods. • In 2018, he published Tales from the Inner City, a book of twenty-five short stories. • The stories describe surreal events occurring in otherwise ordinary urban settings. The student wants to emphasize a similarity between the two books by Shaun Tan. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Shaun Tan’s book Tales from Outer Suburbia, which describes surreal events occurring in otherwise ordinary places, contains fewer short stories than Tales from the Inner City does.
(B) Tales from Outer Suburbia was published in 2008, and Tales from the Inner City was published in 2018.
(C) Unlike Tales from the Inner City, Shaun Tan’s book Tales from Outer Suburbia is set in suburban neighborhoods.
(D) Shaun Tan’s books Tales from Outer Suburbia and Tales from the Inner City both describe surreal events occurring in otherwise ordinary places.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Shaun Tan is an Australian author.
In 2008, he published Tales from Outer Suburbia , a book of fifteen short stories.
The stories describe surreal events occurring in otherwise ordinary suburban neighborhoods.
In 2018, he published Tales from the Inner City , a book of twenty-five short stories.
The stories describe surreal events occurring in otherwise ordinary urban settings.
The student wants to emphasize a similarity between the two books by Shaun Tan. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Shaun Tan’s book Tales from Outer Suburbia , which describes surreal events occurring in otherwise ordinary places, contains fewer short stories than Tales from the Inner City does.
(B) Tales from Outer Suburbia was published in 2008, and Tales from the Inner City was published in 2018.
(C) Unlike Tales from the Inner City , Shaun Tan’s book Tales from Outer Suburbia is set in suburban neighborhoods.
(D) Shaun Tan’s books Tales from Outer Suburbia and Tales from the Inner City both describe surreal events occurring in otherwise ordinary places.
Suggested correct answer: D
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Shaun Tan is an Australian author.</li>
<li>In 2008, he published <em>Tales from Outer Suburbia</em>, a book of fifteen short stories.</li>
<li>The stories describe surreal events occurring in otherwise ordinary suburban neighborhoods.</li>
<li>In 2018, he published <em>Tales from the Inner City</em>, a book of twenty-five short stories.</li>
<li>The stories describe surreal events occurring in otherwise ordinary urban settings.</li>
</ul>
<p>The student wants to emphasize a similarity between the two books by Shaun Tan. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #776 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #773 · Full test · rw · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #772 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) - Atoms in a synchrotron, a type of circular particle accelerator, travel faster and faster until they ______ a desired energy level, at which point they are diverted to collide with a target, smashing the atoms. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) will reach
(B) reach
(C) had reached
(D) are reaching
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Atoms in a synchrotron, a type of circular particle accelerator, travel faster and faster until they ______ blank a desired energy level, at which point they are diverted to collide with a target, smashing the atoms.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: B
Verified stem text <p>Atoms in a synchrotron, a type of circular particle accelerator, travel faster and faster until they <span>______</span><span class="sr-only">blank</span> a desired energy level, at which point they are diverted to collide with a target, smashing the atoms.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #770 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) - Public-awareness campaigns about the need to reduce single-use plastics can be successful, says researcher Kim Borg of Monash University in Australia, when these campaigns give consumers a choice: for example, Japan achieved a 40 percent reduction in plastic-bag use after cashiers were instructed to ask customers whether _______ wanted a bag. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) they
(B) one
(C) you
(D) it
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Public-awareness campaigns about the need to reduce single-use plastics can be successful, says researcher Kim Borg of Monash University in Australia, when these campaigns give consumers a choice: for example, Japan achieved a 40 percent reduction in plastic-bag use after cashiers were instructed to ask customers whether ______ blank wanted a bag.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: A
Verified stem text <p>Public-awareness campaigns about the need to reduce single-use plastics can be successful, says researcher Kim Borg of Monash University in Australia, when these campaigns give consumers a choice: for example, Japan achieved a 40 percent reduction in plastic-bag use after cashiers were instructed to ask customers whether <span>______</span><span class="sr-only">blank</span> wanted a bag.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #766 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Perovskite solar cells convert light into electricity more efficiently than earlier kinds of solar cells, and manufacturing advances have recently made them commercially attractive. One limitation of the cells, however, has to do with their electron transport layer (ETL), through which absorbed electrons must pass. Often the ETL is applied through a process called spin coating, but such ETLs are fairly inefficient at converting input power to output power. André Taylor and colleagues tested a novel spray coating method for applying the ETL. The team produced ETLs of various thicknesses and concluded that spray coating holds promise for improving the power conversion efficiency of ETLs in perovskite solar cells. Which choice best describes data from the graph that support Taylor and colleagues’ conclusion?
(A) Both the ETL applied through spin coating and the ETL applied through spray coating showed a power conversion efficiency greater than 10% at their lowest performing thickness.
(B) The lowest performing ETL applied through spray coating had a higher power conversion efficiency than the highest performing ETL applied through spin coating.
(C) The highest performing ETL applied through spray coating showed a power conversion efficiency of approximately 13%, while the highest performing ETL applied through spin coating showed a power conversion efficiency of approximately 11%.
(D) There was a substantial difference in power conversion efficiency between the lowest and highest performing ETLs applied through spray coating. 14 -
Agriculture Manufacturing Services Year in US in US in US 1800 68 18 13 1900 41 28 31 1950 14 33 53 2012 2 18 80
A) 1900 with the employment by sector in 1950. B) 1800 with the employment by sector in 2012. C) 1900 with the employment by sector in 2012. D) 1800 with the employment by sector in 1900.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.90; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
18 16 14 12 10 8 6 4 2 0 Power conversion efficiency (%) lowest performing highest performing Power Conversion Efficiency of Lowest and Highest Performing Spin-coated and Spray-coated Electron Transport Layers Thickness spray coating spin coating
For each data category, the following bars are shown:
spray coating
spin coating
The data for the 2 categories are as follows:
lowest performing:
spray coating: 15.48%
spin coating: 11.70%
highest performing:
spray coating: 17.26%
spin coating: 13.56%
Perovskite solar cells convert light into electricity more efficiently than earlier kinds of solar cells, and manufacturing advances have recently made them commercially attractive. One limitation of the cells, however, has to do with their electron transport layer (ETL), through which absorbed electrons must pass. Often the ETL is applied through a process called spin coating, but such ETLs are fairly inefficient at converting input power to output power. André Taylor and colleagues tested a novel spray coating method for applying the ETL. The team produced ETLs of various thicknesses and concluded that spray coating holds promise for improving the power conversion efficiency of ETLs in perovskite solar cells.
Which choice best describes data from the graph that support Taylor and colleagues’ conclusion?
(A) Both the ETL applied through spin coating and the ETL applied through spray coating showed a power conversion efficiency greater than 10% at their lowest performing thickness.
(B) The lowest performing ETL applied through spray coating had a higher power conversion efficiency than the highest performing ETL applied through spin coating.
(C) The highest performing ETL applied through spray coating showed a power conversion efficiency of approximately 13%, while the highest performing ETL applied through spin coating showed a power conversion efficiency of approximately 11%.
(D) There was a substantial difference in power conversion efficiency between the lowest and highest performing ETLs applied through spray coating.
Suggested correct answer: B mismatches stored answer "A" -- double check
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text-anchor="top" transform="translate(247.5390625 506.55126953125)">spin coating</text></g></svg><div aria-label="Long description for bar graph titled Power Conversion Efficiency of Lowest and Highest Performing Spin-coated and Spray-coated Electron Transport Layers" class="sr-only" role="region"><ul>
<li>For each data category, the following bars are shown:
<ul>
<li>spray coating</li>
<li>spin coating</li>
</ul>
</li>
<li>The data for the 2 categories are as follows:
<ul>
<li>lowest performing:
<ul>
<li>spray coating: 15.48%</li>
<li>spin coating: 11.70%</li>
</ul>
</li>
<li>highest performing:
<ul>
<li>spray coating: 17.26%</li>
<li>spin coating: 13.56%</li>
</ul>
</li>
</ul>
</li>
</ul></div>
<p>Perovskite solar cells convert light into electricity more efficiently than earlier kinds of solar cells, and manufacturing advances have recently made them commercially attractive. One limitation of the cells, however, has to do with their electron transport layer (ETL), through which absorbed electrons must pass. Often the ETL is applied through a process called spin coating, but such ETLs are fairly inefficient at converting input power to output power. André Taylor and colleagues tested a novel spray coating method for applying the ETL. The team produced ETLs of various thicknesses and concluded that spray coating holds promise for improving the power conversion efficiency of ETLs in perovskite solar cells.</p>
<p>Which choice best describes data from the graph that support Taylor and colleagues’ conclusion?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #765 · Full test · rw · type: grid_in
Source PDF page (reference) Question #763 · Full test · rw · type: mcq
Source PDF page (reference) Question #749 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) If the formation of Earth’s mantle had been purely a product of core differentiation—whereby heavier elements sink toward the core and lighter elements rise—the upper mantle would be depleted of heavy siderophile elements. Siderophiles are much more abundant in the mantle than predicted in that model, however. _______ extraterrestrial material containing siderophiles, likely from asteroid or comet impacts, almost certainly accreted to Earth following core differentiation. Which choice completes the text with the most logical transition?
(A) Thatsaid,
(B) Hence,
(C) For example,
(D) Likewise,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) If some artifacts recovered from excavations of the settlement of Kuulo Kataa, in modern Ghana, date from the thirteenth century CE, that may lend credence to claims that the settlement was founded before or around that time. There is other evidence, however, strongly supporting a fourteenth century CE founding date for Kuulo Kataa. If both the artifact dates and the fourteenth century CE founding date are correct, that would imply that ______ blank
Which choice most logically completes the text?
(A) artifacts from the fourteenth century CE are more commonly recovered than are artifacts from the thirteenth century CE.
(B) the artifacts originated elsewhere and eventually reached Kuulo Kataa through trade or migration.
(C) Kuulo Kataa was founded by people from a different region than had previously been assumed.
(D) excavations at Kuulo Kataa may have inadvertently damaged some artifacts dating to the fourteenth century CE.
Suggested correct answer: B
Verified stem text <p>If some artifacts recovered from excavations of the settlement of Kuulo Kataa, in modern Ghana, date from the thirteenth century CE, that may lend credence to claims that the settlement was founded before or around that time. There is other evidence, however, strongly supporting a fourteenth century CE founding date for Kuulo Kataa. If both the artifact dates and the fourteenth century CE founding date are correct, that would imply that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #748 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) When Chinese director Chloé Zhao accepted the Oscar in 2021 for her film Nomadland, she made Academy Award history. _______ only one other woman, Kathryn Bigelow of the United States, had been named best director at the Oscars, making Zhao the second woman and the first Asian woman to win the award. Which choice completes the text with the most logical transition?
(A) As a result,
(B) Previously,
(C) However,
(D) Likewise,
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) When Chinese director Chloé Zhao accepted the Oscar in 2021 for her film Nomadland , she made Academy Award history. ______ blank only one other woman, Kathryn Bigelow of the United States, had been named best director at the Oscars, making Zhao the second woman and the first Asian woman to win the award.
Which choice completes the text with the most logical transition?
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p>When Chinese director Chloé Zhao accepted the Oscar in 2021 for her film <em>Nomadland</em>, she made Academy Award history. <span>______</span><span class="sr-only">blank</span> only one other woman, Kathryn Bigelow of the United States, had been named best director at the Oscars, making Zhao the second woman and the first Asian woman to win the award.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #747 · Full test · rw · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #746 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The ghazal, a poetic form originating in seventh‑century Arabic poetry, has an intricate structure. The twentieth‑century Kashmiri American poet Agha Shahid Ali explains that each one of a ghazal’s couplets, while adhering to the patterns of rhyme (qafia) and refrain (radif) established in the poem’s opening lines (matla), _______ thematically and logically autonomous, resulting in a poem with “a stringently formal disunity.” Which choice completes the text so that it conforms to the conventions of Standard English?
(A) is
(B) were
(C) C) have been
(D) D) are
Corrected stem text The ghazal, a poetic form originating in seventh‑century Arabic poetry, has an intricate structure. The twentieth‑century Kashmiri American poet Agha Shahid Ali explains that each one of a ghazal’s couplets, while adhering to the patterns of rhyme (qafia) and refrain (radif) established in the poem’s opening lines (matla), _______ thematically and logically autonomous, resulting in a poem with “a stringently formal disunity.” Which choice completes the text so that it conforms to the conventions of Standard English? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #745 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #744 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #736 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In a study of the evolution of DptA and DptB—Diptericin genes encoding antimicrobial peptides that combat pathogens and foster beneficial microbes in fruit flies (Drosophila)—researchers assessed Drosophila melanogaster resistance to pathogenic infections by Providencia rettgeri and Acetobacter sicerae, bacteria common in the flies’ environments. Subjects included flies identified by mutations silencing DptA, DptB, or both DptA and DptB (termed types A, B, and AB, respectively). In conjunction with the observation that resistance to P. rettgeri correlates with DptA activity but is not significantly affected by DptB activity, data in the graph of survival rates post–A. sicerae infection suggest that _______ Which completion of the text is best supported by data in the graph?
(A) DptA confers defense against A. sicerae regardless of the presence of DptB.
(B) DptB protects against only one bacteria species, whereas DptA protects against multiple species.
(C) DptB may have developed as a specific defense against A. sicerae.
(D) defense against A. sicerae is strongest when both DptA and DptB are present.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.41
Bank-match candidate (unverified)
180 160 140 120 100 80 60 40 20 0 REM sleep as % of baseline (mean difference from baseline was not statistically significant) Day 1 Day 2 Fur Seal REM Sleep on Land after an Extended Period in Water Sleep on land Seal B Seal A Seal C
Research suggests that REM sleep in animals is homeostatically regulated: animals compensate for periods of REM sleep deprivation by increasing subsequent REM sleep. When on land, fur seals get enough REM sleep, but during the weeks they’re in the water, they get almost none. In a study of fur seals’ sleep habits, researchers recorded the REM sleep (as a percentage of baseline) of fur seals once they had returned to land. They concluded that REM sleep may not be homeostatically regulated in fur seals, citing as evidence the fact that the seals in the study ______ blank
Which choice most effectively uses data from the graph to complete the text?
(A) didn’t show significantly less REM sleep during the second day after returning to land than they did during the first day.
(B) showed no significant differences from one another in baseline levels of REM sleep.
(C) didn’t consistently demonstrate a significant increase in REM sleep after their period of deprivation in the water.
(D) showed no significant difference between REM sleep after returning to land and REM sleep while in the water.
Suggested correct answer: C
Verified stem text <p></p><svg height="480.84" viewbox="0 0 400 480.84" width="400" xmlns="http://www.w3.org/2000/svg"><g id="ed420550-79eb-48d4-af01-cd27cdd08afd"><defs>
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y="442.84000000000003"></rect><text fill="#000000" font-family="Crimson Text" font-size="19.84" text-anchor="top" transform="translate(191.83001708984375 454.84000000000003)"> Seal C</text></g></svg><p></p>
<p>Research suggests that REM sleep in animals is homeostatically regulated: animals compensate for periods of REM sleep deprivation by increasing subsequent REM sleep. When on land, fur seals get enough REM sleep, but during the weeks they’re in the water, they get almost none. In a study of fur seals’ sleep habits, researchers recorded the REM sleep (as a percentage of baseline) of fur seals once they had returned to land. They concluded that REM sleep may not be homeostatically regulated in fur seals, citing as evidence the fact that the seals in the study <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most effectively uses data from the graph to complete the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #732 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Choctaw/Cherokee artist Jeffrey Gibson turns punching bags used by boxers into art by decorating them with beadwork and elements of Native dressmaking. These elements include leather fringe and jingles, the metal cones that cover the dresses worn in the jingle dance, a women’s dance of the Ojibwe people. Thus, Gibson combines an object commonly associated with masculinity (a punching bag) with art forms traditionally practiced by women in most Native communities (beadwork and dressmaking). In this way, he rejects the division of male and female gender roles. Which choice best describes Gibson’s approach to art, as presented in the text?
(A) He draws from traditional Native art forms to create his original works.
(B) He has been influenced by Native and non-Native artists equally.
(C) He finds inspiration from boxing in designing the dresses he makes.
(D) He rejects expectations about color and pattern when incorporating beadwork.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Choctaw/Cherokee artist Jeffrey Gibson turns punching bags used by boxers into art by decorating them with beadwork and elements of Native dressmaking. These elements include leather fringe and jingles, the metal cones that cover the dresses worn in the jingle dance, a women’s dance of the Ojibwe people. Thus, Gibson combines an object commonly associated with masculinity (a punching bag) with art forms traditionally practiced by women in most Native communities (beadwork and dressmaking). In this way, he rejects the division of male and female gender roles.
Which choice best describes Gibson’s approach to art, as presented in the text?
(A) He draws from traditional Native art forms to create his original works.
(B) He has been influenced by Native and non-Native artists equally.
(C) He finds inspiration from boxing in designing the dresses he makes.
(D) He rejects expectations about color and pattern when incorporating beadwork.
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p>Choctaw/Cherokee artist Jeffrey Gibson turns punching bags used by boxers into art by decorating them with beadwork and elements of Native dressmaking. These elements include leather fringe and jingles, the metal cones that cover the dresses worn in the jingle dance, a women’s dance of the Ojibwe people. Thus, Gibson combines an object commonly associated with masculinity (a punching bag) with art forms traditionally practiced by women in most Native communities (beadwork and dressmaking). In this way, he rejects the division of male and female gender roles.</p>
<p>Which choice best describes Gibson’s approach to art, as presented in the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #731 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The following text is adapted from Oscar Wilde’s 1891 novel The Picture of Dorian Gray. Dorian Gray is taking his first look at a portrait that Hallward has painted of him. Dorian passed listlessly in front of his picture and turned towards it. When he saw it he drew back, and his cheeks flushed for a moment with pleasure. A look of joy came into his eyes, as if he had recognized himself for the first time. He stood there motionless and in wonder, dimly conscious that Hallward was speaking to him, but not catching the meaning of his words. The sense of his own beauty came on him like a revelation. He had never felt it before. According to the text, what is true about Dorian?
(A) He wants to know Hallward’s opinion of the portrait.
(B) He is delighted by what he sees in the portrait.
(C) He prefers portraits to other types of paintings.
(D) He is uncertain of Hallward’s talent as an artist.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The following text is adapted from Oscar Wilde’s 1891 novel The Picture of Dorian Gray . Dorian Gray is taking his first look at a portrait that Hallward has painted of him.
Dorian passed listlessly in front of his picture and turned towards it. When he saw it he drew back, and his cheeks flushed for a moment with pleasure. A look of joy came into his eyes, as if he had recognized himself for the first time. He stood there motionless and in wonder, dimly conscious that Hallward was speaking to him, but not catching the meaning of his words. The sense of his own beauty came on him like a revelation. He had never felt it before.
According to the text, what is true about Dorian?
(A) He wants to know Hallward’s opinion of the portrait.
(B) He is delighted by what he sees in the portrait.
(C) He prefers portraits to other types of paintings.
(D) He is uncertain of Hallward’s talent as an artist.
Suggested correct answer: B
Verified stem text <p>The following text is adapted from Oscar Wilde’s 1891 novel <em>The Picture of Dorian Gray</em>. Dorian Gray is taking his first look at a portrait that Hallward has painted of him.</p>
<p style="padding-left:1em">Dorian passed listlessly in front of his picture and turned towards it. When he saw it he drew back, and his cheeks flushed for a moment with pleasure. A look of joy came into his eyes, as if he had recognized himself for the first time. He stood there motionless and in wonder, dimly conscious that Hallward was speaking to him, but not catching the meaning of his words. The sense of his own beauty came on him like a revelation. He had never felt it before. </p>
<p>According to the text, what is true about Dorian?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #730 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #717 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Which expression is equivalent y+ 12 yx( − 8) to + ? x− 8 xy2 {}^{2} 2 − 8xy
(A) xy + 9 y+ 12
(B) xy 2 {}^{2} 2 + 13 xy − 8y
(C) xy 2 {}^{2} 2 + 13 xy − 8y
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.76
Bank-match candidate (unverified) Which expression is equivalent to 6 x 8 y 2 + 12 x 2 y 2 6 x^{8} y^{2} + 12 x^{2} y^{2} 6 x 8 y 2 + 12 x 2 y 2 ?
(A) 6 x 2 y 2 ( 2 x 6 ) 6 x^{2} y^{2} \left(2 x^{6}\right) 6 x 2 y 2 ( 2 x 6 )
(B) 6 x 2 y 2 ( x 4 ) 6 x^{2} y^{2} \left(x^{4}\right) 6 x 2 y 2 ( x 4 )
(C) 6 x 2 y 2 ( x 6 + 2 ) 6 x^{2} y^{2} \left(x^{6} + 2\right) 6 x 2 y 2 ( x 6 + 2 )
(D) 6 x 2 y 2 ( x 4 + 2 ) 6 x^{2} y^{2} \left(x^{4} + 2\right) 6 x 2 y 2 ( x 4 + 2 )
Suggested correct answer: C
Verified stem text <p>Which expression is equivalent to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><msup><mi>x</mi><mn>8</mn></msup><msup><mi>y</mi><mn>2</mn></msup><mo>+</mo><mn>12</mn><msup><mi>x</mi><mn>2</mn></msup><msup><mi>y</mi><mn>2</mn></msup></mrow><annotation encoding="application/x-tex">6 x^{8} y^{2} + 12 x^{2} y^{2}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.0085em;vertical-align:-0.1944em;"></span><span class="mord">6</span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">8</span></span></span></span></span></span></span></span></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.0085em;vertical-align:-0.1944em;"></span><span class="mord">12</span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #713 · Full test · math · type: grid_inBank-match candidate available
Currently stored (rendered) The function f is defined by fx( ) = a x {}^{x} x +b, where a and b are constants anda > 0. In the xy-plane,the graph of y = fx( ) has a y-interceptat(0, −25) and passes through the point(2, 23) . What is the value of a +b ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.75; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The function f f f is defined by f ( x ) = a x + b f \left(x\right) = a^{x} + b f ( x ) = a x + b , where a a a and b b b are constants. In the x y x y x y -plane, the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) has an x x x -intercept at ( 2 , 0 ) \left(2 , 0\right) ( 2 , 0 ) and a y y y -intercept at ( 0 , − 323 ) \left(0 , - 323\right) ( 0 , − 323 ) . What is the value of b b b ?
Suggested correct answer: -324 mismatches stored answer "-19" -- double check
Verified stem text <p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><msup><mi>a</mi><mi>x</mi></msup><mo>+</mo><mi>b</mi></mrow><annotation encoding="application/x-tex">f \left(x\right) = a^{x} + b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7477em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">a</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6644em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">x</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> are constants. In the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">x y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane, the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> has an <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span>-intercept at <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>2</mn><mo separator="true">,</mo><mn>0</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(2 , 0\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">2</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">0</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> and a <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-intercept at <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>0</mn><mo separator="true">,</mo><mo>−</mo><mn>323</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(0 , - 323\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">0</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">323</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #710 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #709 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Each of the dot plots shown represents the number of glue sticks brought in by each student for two classes, class A and class B. Which statement best compares the standard deviations of the numbers of glue sticks brought in by each student for these two classes?
(A) The standard deviation of the number of glue sticks brought in by each student for class A is less than the standard deviation of the number of glue sticks brought in by each student for class B.
(B) The standard deviation of the number of glue sticks brought in by each student for class A is equal to the standard deviation of the number of glue sticks brought in by each student for class B.
(C) The standard deviation of the number of glue sticks brought in by each student for class A is greater than the standard deviation of the number of glue sticks brought in by each student for class B.
(D) There is not enough information to compare these standard deviations.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.73; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
For the dot plot titled Class A:
The number line ranges from 1 to 7 in increments of 1.
The data for the dot plot are as follows:
1: 1 dot
2: 1 dot
3: 3 dots
4: 4 dots
5: 5 dots
6: 6 dots
7: 7 dots
For the dot plot titled Class B:
The number line ranges from 14 to 20 in increments of 1.
The data for the dot plot are as follows:
14: 1 dot
15: 1 dot
16: 3 dots
17: 4 dots
18: 5 dots
19: 6 dots
20: 7 dots
Each of the dot plots shown represents the number of glue sticks brought in by each student for two classes, class A and class B. Which statement best compares the standard deviations of the numbers of glue sticks brought in by each student for these two classes?
(A) The standard deviation of the number of glue sticks brought in by each student for class A is less than the standard deviation of the number of glue sticks brought in by each student for class B.
(B) The standard deviation of the number of glue sticks brought in by each student for class A is equal to the standard deviation of the number of glue sticks brought in by each student for class B.
(C) The standard deviation of the number of glue sticks brought in by each student for class A is greater than the standard deviation of the number of glue sticks brought in by each student for class B.
(D) There is not enough information to compare these standard deviations.
Suggested correct answer: B
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d="M123.11,116.407a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,123.11,116.407Z"></path><path d="M123.11,102.549a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,123.11,102.549Z"></path><path d="M123.11,88.69a3.78,3.78,0,1,1-3.778-3.78A3.776,3.776,0,0,1,123.11,88.69Z"></path><path d="M123.11,74.828a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,123.11,74.828Z"></path><path d="M123.11,60.971a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,123.11,60.971Z"></path><path d="M233.007,116.407a3.78,3.78,0,1,1-3.779-3.78A3.778,3.778,0,0,1,233.007,116.407Z"></path><circle cx="255.174" cy="116.407" r="3.78"></circle><circle cx="281.123" cy="116.407" r="3.78"></circle><circle cx="281.123" cy="102.549" r="3.78"></circle><path d="M284.9,88.69a3.78,3.78,0,1,1-3.78-3.78A3.777,3.777,0,0,1,284.9,88.69Z"></path><path d="M310.853,116.407a3.78,3.78,0,1,1-3.778-3.78A3.778,3.778,0,0,1,310.853,116.407Z"></path><path d="M310.853,102.549a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,310.853,102.549Z"></path><path d="M310.853,88.69a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,310.853,88.69Z"></path><path d="M310.853,74.828a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,310.853,74.828Z"></path><path d="M388.694,116.407a3.78,3.78,0,1,1-3.779-3.78A3.778,3.778,0,0,1,388.694,116.407Z"></path><path d="M388.694,102.549a3.78,3.78,0,1,1-3.779-3.78A3.78,3.78,0,0,1,388.694,102.549Z"></path><path d="M388.694,88.69a3.78,3.78,0,1,1-3.779-3.78A3.777,3.777,0,0,1,388.694,88.69Z"></path><path d="M388.694,74.828a3.78,3.78,0,1,1-3.779-3.78A3.78,3.78,0,0,1,388.694,74.828Z"></path><path d="M388.694,60.971a3.78,3.78,0,1,1-3.779-3.78A3.78,3.78,0,0,1,388.694,60.971Z"></path><path d="M388.694,47.112a3.78,3.78,0,1,1-3.779-3.78A3.777,3.777,0,0,1,388.694,47.112Z"></path><path d="M388.694,33.25a3.78,3.78,0,1,1-3.779-3.78A3.78,3.78,0,0,1,388.694,33.25Z"></path><path d="M362.747,116.407a3.78,3.78,0,1,1-3.778-3.78A3.778,3.778,0,0,1,362.747,116.407Z"></path><path d="M362.747,102.549a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,362.747,102.549Z"></path><path d="M362.747,88.69a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,362.747,88.69Z"></path><path d="M362.747,74.828a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,362.747,74.828Z"></path><path d="M362.747,60.971a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,362.747,60.971Z"></path><path d="M362.747,47.112a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,362.747,47.112Z"></path><path d="M336.8,116.407a3.78,3.78,0,1,1-3.778-3.78A3.778,3.778,0,0,1,336.8,116.407Z"></path><path d="M336.8,102.549a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,336.8,102.549Z"></path><path d="M336.8,88.69a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,336.8,88.69Z"></path><path d="M336.8,74.828a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,336.8,74.828Z"></path><path d="M336.8,60.971a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,336.8,60.971Z"></path><line x1="398.299" y1="131.346" x2="214.159" y2="131.346" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="358.964" y1="125.676" x2="358.964" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="229.224" y1="125.676" x2="229.224" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="384.911" y1="125.676" x2="384.911" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="255.171" y1="125.676" x2="255.171" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="281.121" y1="125.676" x2="281.121" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="307.07" y1="125.676" x2="307.07" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line><line x1="333.017" y1="125.676" x2="333.017" y2="137.016" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="0.945"></line></g></svg><div role="region" aria-label="Long description for 2 dot plots titled Class A and Class B" class="sr-only"><ul>
<li>For the dot plot titled Class A:<br />
<ul>
<li>The number line ranges from 1 to 7 in increments of 1.</li>
<li>The data for the dot plot are as follows:<br />
<ul>
<li>1: 1 dot</li>
<li>2: 1 dot</li>
<li>3: 3 dots</li>
<li>4: 4 dots</li>
<li>5: 5 dots</li>
<li>6: 6 dots</li>
<li>7: 7 dots</li>
</ul>
</li>
</ul>
</li>
<li>For the dot plot titled Class B:<br />
<ul>
<li>The number line ranges from 14 to 20 in increments of 1.</li>
<li>The data for the dot plot are as follows:<br />
<ul>
<li>14: 1 dot</li>
<li>15: 1 dot</li>
<li>16: 3 dots</li>
<li>17: 4 dots</li>
<li>18: 5 dots</li>
<li>19: 6 dots</li>
<li>20: 7 dots</li>
</ul>
</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">Each of the dot plots shown represents the number of glue sticks brought in by each student for two classes, class A and class B. Which statement best compares the standard deviations of the numbers of glue sticks brought in by each student for these two classes?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #708 · Full test · math · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #707 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) TriangleFGH is similar to triangle JKL, where angle F corresponds to angle J and angles G and K 308 are right angles. Ifsin ( F ) = , what is the value of 317 sin ( ) J ? 75
(A) 308
(B) 317
(C) 317
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.80
Bank-match candidate (unverified) Triangle F G H F G H F G H is similar to triangle J K L J K L J K L , where angle F F F corresponds to angle J J J and angles G G G and K K K are right angles. If sin ( F ) = 308 317 \sin \left(F\right) = \dfrac{308}{317} sin ( F ) = 317 308 , what is the value of sin ( J ) \sin \left(J\right) sin ( J ) ?
(A) 75 317 \dfrac{75}{317} 317 75
(B) 308 317 \dfrac{308}{317} 317 308
(C) 317 308 \dfrac{317}{308} 308 317
(D) 317 75 \dfrac{317}{75} 75 317
Suggested correct answer: B
Verified stem text <p style="text-align: left;">Triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi><mi>G</mi><mi>H</mi></mrow><annotation encoding="application/x-tex">F G H</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span><span class="mord mathnormal">G</span><span class="mord mathnormal" style="margin-right:0.0813em;">H</span></span></span></span> is similar to triangle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>J</mi><mi>K</mi><mi>L</mi></mrow><annotation encoding="application/x-tex">J K L</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0962em;">J</span><span class="mord mathnormal" style="margin-right:0.0715em;">K</span><span class="mord mathnormal">L</span></span></span></span>, where angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi></mrow><annotation encoding="application/x-tex">F</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span> corresponds to angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>J</mi></mrow><annotation encoding="application/x-tex">J</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0962em;">J</span></span></span></span> and angles <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>G</mi></mrow><annotation encoding="application/x-tex">G</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">G</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>K</mi></mrow><annotation encoding="application/x-tex">K</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0715em;">K</span></span></span></span> are right angles. If <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>sin</mi><mo></mo><mrow><mo fence="true">(</mo><mi>F</mi><mo fence="true">)</mo></mrow><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>308</mn><mn>317</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\sin \left(F\right) = \dfrac{308}{317}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mop">sin</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">317</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">308</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span>, what is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>sin</mi><mo></mo><mrow><mo fence="true">(</mo><mi>J</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">\sin \left(J\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mop">sin</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal" style="margin-right:0.0962em;">J</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #706 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #705 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #701 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Which ordered pair( xy, ) is a solution to the given system of equations?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.80
Bank-match candidate (unverified) x + 7 = 10 x + 7 = 10 x + 7 = 10
( x + 7 ) 2 = y \left(x + 7\right)^{2} = y ( x + 7 ) 2 = y
Which ordered pair ( x , y ) \left(x , y\right) ( x , y ) is a solution to the given system of equations?
(A) ( 3 , 100 ) \left(3 , 100\right) ( 3 , 100 )
(B) ( 3 , 3 ) \left(3 , 3\right) ( 3 , 3 )
(C) ( 3 , 10 ) \left(3 , 10\right) ( 3 , 10 )
(D) ( 3 , 70 ) \left(3 , 70\right) ( 3 , 70 )
Suggested correct answer: A
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>+</mo><mn>7</mn><mo>=</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">x + 7 = 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">7</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span></p>
<p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mrow><mo fence="true">(</mo><mi>x</mi><mo>+</mo><mn>7</mn><mo fence="true">)</mo></mrow><mn>2</mn></msup><mo>=</mo><mi>y</mi></mrow><annotation encoding="application/x-tex">\left(x + 7\right)^{2} = y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.204em;vertical-align:-0.25em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">7</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.954em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span></p>
<p style="text-align: left;">Which ordered pair <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(x , y\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> is a solution to the given system of equations?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #697 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #696 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Live east Live west of the river of the river Total Less than 17 11 28 40 years old At least 18 89 107 40 years old Total 35 100 135 The table summarizes members of a local organization by age and whether they live east or west of the river. If a member of the organization is selected at random, what is the probability that the selected member is at least 40 years old? 28
(A) 35
(B) 100
(C) 107
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified)
Customer Purchases at a Gas Station
Beverage purchased
Beverage not purchased
Total
Gasoline purchased
60
25
85
Gasoline not purchased
35
15
50
Total
90
40
135
On Tuesday, a local gas station had 135 customers. The table above summarizes whether or not the customers on Tuesday purchased gasoline, a beverage, both, or neither. Based on the data in the table, what is the probability that a gas station customer selected at random on that day did not purchase gasoline?
(D)
50 135 \dfrac{50}{135} 135 50
Suggested correct answer: D
Verified stem text <div class="stimulus_reference ">
<div class="passage ">
<div class="prose style:1 "></div>
</div>
</div>
<div class="tcp-3d646db2-b001-4827-83f2-417c86f7484a">
<table class="table_WithBorder tcp-a941e991-39e6-4be9-9285-30afb9eef87b">Customer Purchases at a Gas Station
<tbody><tr><td class="tcp-b3b44fc5-0192-4460-92d6-cb8f4617e526"></td>
<td class="tcp-9ddeecbb-f576-47ad-8f8f-bd3f0455fc76">Beverage purchased</td>
<td class="tcp-369fffcd-74f2-4334-be88-49d38997b145">Beverage not purchased</td>
<td class="tcp-7a96acad-3f1f-43e8-8849-4c77281bd6d9">Total</td>
</tr><tr><td class="tcp-5704d7b1-9842-4e18-a849-3d71ef786707">Gasoline purchased</td>
<td class="tcp-624b53eb-3070-471e-b21e-63857d166f58">60</td>
<td class="tcp-59e1376b-53ec-472d-94f8-67fe0c247692">25</td>
<td class="tcp-6980a7d3-9f73-4e61-9008-052b49dd9c18">85</td>
</tr><tr><td class="tcp-643d159f-6713-4dc6-b71f-0672e6226ae9">Gasoline not purchased</td>
<td class="tcp-56d5c23f-2d01-448b-a5c1-b12b68fa8f13">35</td>
<td class="tcp-1d3f01d5-8123-4584-985b-821f6d4d519e">15</td>
<td class="tcp-7ae4aa9e-649f-40dd-b482-bde562913196">50</td>
</tr><tr><td class="tcp-fc83c8d2-278d-421a-b1bb-fb829fcb6fb8">Total</td>
<td class="tcp-fa6a1bae-d732-43a6-bce0-44788fc6783d">90</td>
<td class="tcp-09b65877-4e14-495c-8834-42fd0d590ee4">40</td>
<td class="tcp-9743194a-b19c-488a-bd35-2ef1cedd5f1d">135</td>
</tr></tbody></table><p class="stem_paragraph ">On Tuesday, a local gas station had 135 customers. The table above summarizes whether or not the customers on Tuesday purchased gasoline, a beverage, both, or neither. Based on the data in the table, what is the probability that a gas station customer selected at random on that day did <span class="underline"><span class=" underline ">not</span></span> purchase gasoline?</p></div> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #695 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #694 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #691 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #690 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #681 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #678 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The circle shown has center O, circumference144 π, and diametersPR andQS . The length of arcPS is twice the length of arcPQ . What is the length of arcQR ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
The circle above with center O O O has a circumference of 36. What is the length of minor arc A C A C A C ?
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <div class="stimulus_reference ">
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" alt="The figure presents a circle with center O. Points A, and C are indicated on the circle, creating minor arc A, C. A diameter is drawn from point A to a point on the other side of the circle. Similarly, a diameter is drawn from point C to a point on the other side of the circle. The two lines intersect at the origin, forming a right angle at angle A, O C" /></div>
</div>
<p class="stem_paragraph ">The circle above with center <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>O</mi></mrow><annotation encoding="application/x-tex">O</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">O</span></span></span></span> has a circumference of 36. What is the length of minor arc <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mi>C</mi></mrow><annotation encoding="application/x-tex">A C</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #676 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #671 · Full test · math · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #670 · Full test · math · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #668 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #659 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) With the development of new technologies that use natural resources more efficiently, the overall consumption of those resources might be expected to decrease. Economists have observed that improvements in efficiency often correlate negatively with resource _______ efficiency gains, lowering the cost of use, may increase demand to the extent that resource consumption ultimately rises. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) conservation, though,
(B) conservation; though
(C) conservation, though;
(D) conservation, though
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified) The alga species Chlorella vulgaris is very efficient at making oxygen. For this reason, scientists are currently exploring ways to use this species in space. C. vulgaris might be used, for example, to build future biological air exchange systems that ______ blank oxygen for astronauts.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: C
Verified stem text <p>The alga species <em>Chlorella vulgaris</em> is very efficient at making oxygen. For this reason, scientists are currently exploring ways to use this species in space. <em>C. vulgaris</em> might be used, for example, to build future biological air exchange systems that <span>______</span><span class="sr-only">blank</span> oxygen for astronauts. </p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #658 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) 25 In the late nineteenth and early twentieth centuries, automobiles were commonly referred to as horseless carriages after the older technology they still resembled. Known as the Brass Era, this period in automotive design is remembered for its grandeur and artistry, its vehicles _______ by collectors for their ornate detailing and gleaming brass fittings. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) are highly prized
(B) had been highly prized
(C) highly prized
(D) were highly prized
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified) In his groundbreaking book Bengali Harlem and the Lost Histories of South Asian America , Vivek Bald uses newspaper articles, census records, ships’ logs, and memoirs to tell the ______ blank who made New York City their home in the early twentieth century.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) story’s of the South Asian immigrants
(B) story’s of the South Asian immigrants’
(C) stories of the South Asian immigrants
(D) stories’ of the South Asian immigrant’s
Suggested correct answer: C
Verified stem text <p>In his groundbreaking book <em>Bengali Harlem and the Lost Histories of South Asian America</em>, Vivek Bald uses newspaper articles, census records, ships’ logs, and memoirs to tell the <span>______</span><span class="sr-only">blank</span> who made New York City their home in the early twentieth century.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #654 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #651 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Aptamers—synthetic DNA or RNA molecules that bind to target molecules—can be used to test for foodborne bacterial pathogens, though their specificity (the probability of returning a negative result in the absence of the focal pathogen) in real-world foods has been unclear. Sandeep Somvanshi et al. fabricated test paper incorporating aptamers targeting strain O157:H7 of the bacteria Escherichiacoli; the paper shifts from pink to purple as the aptamers bind to target molecules. Somvanshi et al. tested the paper in store-bought pear juice they treated with E.coli O157:H7, other strains of E.coli, or other bacteria species. Following exposure, the paper from the O157:H7 test was purple while papers from the other tests were pink, suggesting that _______ Which choice most logically completes the text?
(A) aptamer-based tests in real-world foods are more likely to show a high degree of specificity if the focal pathogen is E.coli O157:H7 than if the focal pathogen is another strain of E.coli or another species.
(B) uncertainty about the specificity of aptamer-based tests for pathogens in real-world foods may be due to the similarity between E.coli O157:H7 and other E.coli strains.
(C) the specificity of the tests in a real-world food was unaffected by the aptamers’ tendency to bind to different strains of E.coli.
(D) the aptamers successfully bound to E.coli O157:H7 and the tests displayed a high degree of specificity in a real-world food.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.42
Bank-match candidate (unverified) Birds of many species ingest foods containing carotenoids, pigmented molecules that are converted into feather coloration. Coloration tends to be especially saturated in male birds’ feathers, and because carotenoids also confer health benefits, the deeply saturated colors generally serve to communicate what is known as an honest signal of a bird’s overall fitness to potential mates. However, ornithologist Allison J. Shultz and others have found that males in several species of the tanager genus Ramphocelus use microstructures in their feathers to manipulate light, creating the appearance of deeper saturation without the birds necessarily having to maintain a carotenoid-rich diet. These findings suggest that ______ blank
Which choice most logically completes the text?
(A) individual male tanagers can engage in honest signaling without relying on carotenoid consumption.
(B) feather microstructures may be less effective than deeply saturated feathers for signaling overall fitness.
(C) scientists have yet to determine why tanagers have a preference for mates with colorful appearances.
(D) a male tanager’s appearance may function as a dishonest signal of the individual’s overall fitness.
Suggested correct answer: D
Verified stem text <p>Birds of many species ingest foods containing carotenoids, pigmented molecules that are converted into feather coloration. Coloration tends to be especially saturated in male birds’ feathers, and because carotenoids also confer health benefits, the deeply saturated colors generally serve to communicate what is known as an honest signal of a bird’s overall fitness to potential mates. However, ornithologist Allison J. Shultz and others have found that males in several species of the tanager genus <em>Ramphocelus</em> use microstructures in their feathers to manipulate light, creating the appearance of deeper saturation without the birds necessarily having to maintain a carotenoid-rich diet. These findings suggest that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #647 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) “Mrs. Spring Fragrance” is a 1912 short story by Sui Sin Far. In the story, Mrs. Spring Fragrance, a Chinese immigrant living in Seattle, is traveling in California. In letters to her husband and friend, she demonstrates her concern for what’s happening at her home in Seattle while she is away: _______ Which quotation from Mrs. Spring Fragrance’s letters most effectively illustrates the claim?
(A) “My honorable cousin is preparing for the Fifth Moon Festival, and wishes me to compound for the occasion some American ‘fudge,’ for which delectable sweet, made by my clumsy hands, you have sometimes shown a slight prejudice.”
(B) “Next week I accompany Ah Oi to the beauteous town of San José. There will we be met by the son of the Illustrious Teacher.”
(C) “Forget not to care for the cat, the birds, and the flowers. Do not eat too quickly nor fan too vigorously now that the weather is warming.”
(D) “I am enjoying a most agreeable visit, and American friends, as also our own, strive benevolently for the accomplishment of my pleasure.”
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) “Mrs. Spring Fragrance” is a 1912 short story by Sui Sin Far. In the story, Mrs. Spring Fragrance, a Chinese immigrant living in Seattle, is traveling in California. In letters to her husband and friend, she demonstrates her concern for what’s happening at her home in Seattle while she is away: ______ blank
Which quotation from Mrs. Spring Fragrance’s letters most effectively illustrates the claim?
(A) “My honorable cousin is preparing for the Fifth Moon Festival, and wishes me to compound for the occasion some American ‘fudge,’ for which delectable sweet, made by my clumsy hands, you have sometimes shown a slight prejudice.”
(B) “Next week I accompany Ah Oi to the beauteous town of San José. There will we be met by the son of the Illustrious Teacher.”
(C) “Forget not to care for the cat, the birds, and the flowers. Do not eat too quickly nor fan too vigorously now that the weather is warming.”
(D) “I am enjoying a most agreeable visit, and American friends, as also our own, strive benevolently for the accomplishment of my pleasure.”
Suggested correct answer: C
Verified stem text <p>“Mrs. Spring Fragrance” is a 1912 short story by Sui Sin Far. In the story, Mrs. Spring Fragrance, a Chinese immigrant living in Seattle, is traveling in California. In letters to her husband and friend, she demonstrates her concern for what’s happening at her home in Seattle while she is away: <span>______</span><span class="sr-only">blank</span></p>
<p>Which quotation from Mrs. Spring Fragrance’s letters most effectively illustrates the claim?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #643 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In the 1960s, Gloria Richardson led a movement to promote racial equality. Her involvement in this effort was inspired by her daughter, Donna Richardson. In 1961, Donna joined protests organized by the Student Nonviolent Coordinating Committee in Cambridge, Maryland. Following her daughter, Gloria joined these protests too. Gloria soon became the cochair of the Cambridge Nonviolent Action Committee. She was also the leader of what became known as the Cambridge movement. According to the text, what did Gloria Richardson lead?
(A) The Cambridge movement
(B) Her daughter Donna’s high school
(C) Protests to support environmental protections
(D) A new business in Cambridge, Maryland
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.37
Bank-match candidate (unverified) In 1885, Chinese-born California resident Mary Tape became a hero of the Asian American civil rights movement. In January of that year, she won an antidiscrimination case in the California Supreme Court. ______ blank in April, she wrote an open letter criticizing her local board of education for discrimination. Both actions are remembered today as historic stands against racism.
Which choice completes the text with the most logical transition?
Suggested correct answer: A
Verified stem text <p>In 1885, Chinese-born California resident Mary Tape became a hero of the Asian American civil rights movement. In January of that year, she won an antidiscrimination case in the California Supreme Court. <span>______</span><span class="sr-only">blank</span> in April, she wrote an open letter criticizing her local board of education for discrimination. Both actions are remembered today as historic stands against racism.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #642 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Individual elephants and Arctic herbivores such as caribou tend to have fixed geographic ranges throughout their lifetimes, which had prompted some researchers to speculate that the Arctic woolly mammoth, an extinct elephantid, might have exhibited similar behavior. Mammoth tusks grew in sequential layers, incorporating ingested minerals and organics, and so each ivory stratum reflects the ratio of strontium isotopes (87 {}^{87} 87 Sr/86 {}^{86} 86 Sr) in the local environment; thus, the sequence of strata shows where the animal roamed during life. Recent analysis of the strontium ratios in the strata of one Arctic woolly mammoth tusk in relation to the geographic distribution of strontium ratios in the environment shows the animal’s range begin to expand as it reached sexual maturity, only to contract again in its final 1.5 years. Which choice best describes the function of the underlined statement in the text as a whole?
(A) It discusses a characteristic shared by certain animals in order to explain why researchers raised a possibility that turned out not to be supported by data described later in the text.
(B) It illustrates a pattern of behavior among certain animals in order to present a theory about exceptions to that pattern that is weakened by a finding described later in the text.
(C) It describes a similarity in the behavior of certain animals in order to show why a method described later in the text did not reveal whether another animal also showed that behavior.
(D) It introduces a trait shared by certain animals in order to contextualize a hypothesis about the origin of that trait that is advanced later in the text.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) “How lifelike are they?” Many computer animators prioritize this question as they strive to create ever more realistic environments and lighting. Generally, while characters in computer-animated films appear highly exaggerated, environments and lighting are carefully engineered to mimic reality. But some animators, such as Pixar’s Sanjay Patel, are focused on a different question. Rather than asking first whether the environments and lighting they’re creating are convincingly lifelike, Patel and others are asking whether these elements reflect their films’ unique stories.
Which choice best describes the function of the underlined question in the text as a whole?
(A) It reflects a primary goal that many computer animators have for certain components of the animations they produce.
(B) It represents a concern of computer animators who are more interested in creating unique backgrounds and lighting effects than realistic ones.
(C) It conveys the uncertainty among many computer animators about how to create realistic animations using current technology.
(D) It illustrates a reaction that audiences typically have to the appearance of characters created by computer animators.
Suggested correct answer: A
Verified stem text <p><span role="region" aria-label="Referenced Content"><u>“How lifelike are they?”</u></span> Many computer animators prioritize this question as they strive to create ever more realistic environments and lighting. Generally, while characters in computer-animated films appear highly exaggerated, environments and lighting are carefully engineered to mimic reality. But some animators, such as Pixar’s Sanjay Patel, are focused on a different question. Rather than asking first whether the environments and lighting they’re creating are convincingly lifelike, Patel and others are asking whether these elements reflect their films’ unique stories.</p>
<p>Which choice best describes the function of the underlined question in the text as a whole?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #621 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #620 · Full test · rw · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #619 · Full test · rw · type: mcqno answer key Bank-match candidate available
Source PDF page (reference) Question #612 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Maximum Height of Maple Trees When Fully Grown
Maximum Native to Tree type height (feet) North America Sugarmaple 75 yes Silvermaple 70 yes Redmaple 60 yes Japanese maple 25 no Norwaymaple 50 no
For a school project, a forestry student needs to recommend a maple tree that is native to North America and won’t grow more than 60 feet in height. Based on the characteristics of five common maple trees, she has decided to select a _______ Which choice most effectively uses data from the table to complete the text?
(A) silvermaple.
(B) sugarmaple.
(C) redmaple.
(D) Norwaymaple.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.96; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
Maximum Height of Maple Trees When Fully Grown
Tree type Maximum height (feet) Native to North America Sugar maple 75 yes Silver maple 70 yes Red maple 60 yes Japanese maple 25 no Norway maple 50 no
For a school project, a forestry student needs to recommend a maple tree that is native to North America and won’t grow more than 60 feet in height. Based on the characteristics of five common maple trees, she has decided to select a ______ blank
Which choice most effectively uses data from the table to complete the text?
Suggested correct answer: C mismatches stored answer "A" -- double check
Verified stem text <p></p><table class="gdr"><p style="text-align: center;">Maximum Height of Maple Trees When Fully Grown</p><thead><tr><th scope="col" style="text-align: center; vertical-align: bottom;">Tree type</th><th scope="col" style="text-align: center; vertical-align: bottom;">Maximum height (feet)</th><th scope="col" style="text-align: center; vertical-align: bottom;">Native to North America</th></tr></thead><tbody><tr><th scope="row" style="text-align: left;">Sugar maple</th><td style="text-align: center;">75</td><td>yes</td></tr><tr><th scope="row" style="text-align: left;">Silver maple</th><td style="text-align: center;">70</td><td>yes</td></tr><tr><th scope="row" style="text-align: left;">Red maple</th><td style="text-align: center;">60</td><td>yes</td></tr><tr><th scope="row" style="text-align: left;">Japanese maple</th><td style="text-align: center;">25</td><td>no</td></tr><tr><th scope="row" style="text-align: left;">Norway maple</th><td style="text-align: center;">50</td><td>no</td></tr></tbody></table><p></p>
<p>For a school project, a forestry student needs to recommend a maple tree that is native to North America and won’t grow more than 60 feet in height. Based on the characteristics of five common maple trees, she has decided to select a <span>______</span><span class="sr-only">blank</span> </p>
<p>Which choice most effectively uses data from the table to complete the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #611 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #610 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Utah is home to Pando, a colony of about 47,000 quaking aspen trees that all share a single root system. Pando is one of the largest single organisms by mass on Earth, but ecologists are worried that its growth is declining in part because of grazing by animals. The ecologists say that strong fences could prevent deer from eating young trees and help Pando start thriving again. According to the text, why are ecologists worried about Pando?
(A) It isn’t growing at the same rate it used to.
(B) It isn’t producing young trees anymore.
(C) It can’t grow into new areas because it is blocked by fences.
(D) Its root system can’t support many more new trees.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Utah is home to Pando, a colony of about 47,000 quaking aspen trees that all share a single root system. Pando is one of the largest single organisms by mass on Earth, but ecologists are worried that its growth is declining in part because of grazing by animals. The ecologists say that strong fences could prevent deer from eating young trees and help Pando start thriving again.
According to the text, why are ecologists worried about Pando?
(A) It isn’t growing at the same rate it used to.
(B) It isn’t producing young trees anymore.
(C) It can’t grow into new areas because it is blocked by fences.
(D) Its root system can’t support many more new trees.
Suggested correct answer: A
Verified stem text <p>Utah is home to Pando, a colony of about 47,000 quaking aspen trees that all share a single root system. Pando is one of the largest single organisms by mass on Earth, but ecologists are worried that its growth is declining in part because of grazing by animals. The ecologists say that strong fences could prevent deer from eating young trees and help Pando start thriving again.</p>
<p>According to the text, why are ecologists worried about Pando?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #608 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In response to concerns that some recent financial crises were exacerbated by consumers misunderstanding risks associated with credit cards, loans, and other financial products, policymakers in many countries have instituted risk-disclosure requirements on sellers of those products. Enrique Seira et al. investigated a variety of risk-disclosure messages sent to thousands of credit card customers and found that the messages had only small and short-lived effects on behavior. Seira et al. asserted that such effects may nevertheless be worth pursuing, given the negligible cost of messaging. Which choice best describes the function of the underlined portion in the text as a whole?
(A) It notes a factor that led Seira et al. to not dismiss risk-disclosure messaging altogether despite their evidence of its limited utility.
(B) It acknowledges a type of risk-disclosure messaging that Seira et al. may not have fully accounted for in their study.
(C) It describes a consideration that explains why Seira et al. recommended risk-disclosure messaging even though its effects may be small relative to its costs.
(D) It points out a circumstance that Seira et al. conceded may make risk-disclosure messaging more effective than their study suggests.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) “How lifelike are they?” Many computer animators prioritize this question as they strive to create ever more realistic environments and lighting. Generally, while characters in computer-animated films appear highly exaggerated, environments and lighting are carefully engineered to mimic reality. But some animators, such as Pixar’s Sanjay Patel, are focused on a different question. Rather than asking first whether the environments and lighting they’re creating are convincingly lifelike, Patel and others are asking whether these elements reflect their films’ unique stories.
Which choice best describes the function of the underlined question in the text as a whole?
(A) It reflects a primary goal that many computer animators have for certain components of the animations they produce.
(B) It represents a concern of computer animators who are more interested in creating unique backgrounds and lighting effects than realistic ones.
(C) It conveys the uncertainty among many computer animators about how to create realistic animations using current technology.
(D) It illustrates a reaction that audiences typically have to the appearance of characters created by computer animators.
Suggested correct answer: A
Verified stem text <p><span role="region" aria-label="Referenced Content"><u>“How lifelike are they?”</u></span> Many computer animators prioritize this question as they strive to create ever more realistic environments and lighting. Generally, while characters in computer-animated films appear highly exaggerated, environments and lighting are carefully engineered to mimic reality. But some animators, such as Pixar’s Sanjay Patel, are focused on a different question. Rather than asking first whether the environments and lighting they’re creating are convincingly lifelike, Patel and others are asking whether these elements reflect their films’ unique stories.</p>
<p>Which choice best describes the function of the underlined question in the text as a whole?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #606 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The following text is adapted from Cynthia Kadohata’s 2004 novel Kira-Kira. [Uncle Katsuhisa] was as loud as my father was quiet. Even when he wasn’t talking, he made a lot of noise, clearing his throat and sniffing and tapping his fingers. ©2004 by Cynthia Kadohata Which choice best describes the function of the underlined sentence?
(A) It lists the kinds of topics Uncle Katsuhisa enjoys discussing.
(B) It suggests that Uncle Katsuhisa dislikes meeting new people.
(C) It contrasts Uncle Katsuhisa with the narrator’s father.
(D) It describes a conversation between the narrator and the narrator’s father.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) The following text is from Srimati Svarna Kumari Devi’s 1894 novel The Fatal Garland (translated by A. Christina Albers in 1910). Shakti is walking near a riverbank that she visited frequently during her childhood.
She crossed the woods she knew so well. The trees seemed to extend their branches like welcoming arms. They greeted her as an old friend. Soon she reached the river-side.
Which choice best describes the function of the underlined portion in the text as a whole?
(A) It suggests that Shakti feels uncomfortable near the river.
(B) It indicates that Shakti has lost her sense of direction in the woods.
(C) It emphasizes Shakti’s sense of belonging in the landscape.
(D) It conveys Shakti’s appreciation for her long-term friendships.
Suggested correct answer: C
Verified stem text <p>The following text is from Srimati Svarna Kumari Devi’s 1894 novel <em>The Fatal Garland</em> (translated by A. Christina Albers in 1910). Shakti is walking near a riverbank that she visited frequently during her childhood.</p>
<p>She crossed the woods she knew so well. <span role="region" aria-label="Referenced Content"><u>The trees seemed to extend their branches like welcoming arms.</u></span> They greeted her as an old friend. Soon she reached the river-side.</p>
<p>Which choice best describes the function of the underlined portion in the text as a whole? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #601 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The following text is adapted from Ida B. Wells’s 1970 autobiography A Crusade for Justice. Mr. Watts is a reference to George Frederic Watts, an English painter. [Manchester’s] art galleries are so arranged that the name of every picture is plainly seen and one has no need of a catalogue to pick out the name and the artist. This is a convenience to the general public, which other art galleries, which shall be nameless, might copy to advantage. To her treasure of art Manchester has added Mr. Watts’ latest picture, the Good Samaritan. ©1970 by the University of Chicago Press As used in the text, what does the word “arranged” most nearly mean?
(A) Organized
(B) Ranked
(C) Scheduled
(D) Discussed
Corrected stem text The following text is adapted from Ida B. Wells’s 1970 autobiography A Crusade for Justice. Mr. Watts is a reference to George Frederic Watts, an English painter. [Manchester’s] art galleries are so §U§arranged§ that the name of every picture is plainly seen and one has no need of a catalogue to pick out the name and the artist. This is a convenience to the general public, which other art galleries, which shall be nameless, might copy to advantage. To her treasure of art Manchester has added Mr. Watts’ latest picture, the Good Samaritan. ©1970 by the University of Chicago Press As used in the text, what does the word “arranged” §IMG§/full-test-images/test-9-rw-1-1-inline-0.png§ most nearly mean? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #600 · Full test · math · type: grid_in
Currently stored (rendered) - The quadratic function g models the depth, in meters, below the surface of the water of a seal t minutes after the seal entered the water during a dive. The function estimates that the seal reached its maximum depth of 302.4 meters 6 minutes after it entered the water and then reached the surface of the water 12 minutes after it entered the water. Based on the function, what was the estimated depth, to the nearest meter, of the seal 10 minutes after it entered the water? The SAT.
Corrected stem text - The quadratic function g models the depth, in meters, below the surface of the water of a seal t minutes after the seal entered the water during a dive. The function estimates that the seal reached its maximum depth of 302.4 meters 6 minutes after it entered the water and then reached the surface of the water 12 minutes after it entered the water. Based on the function, what was the estimated depth, to the nearest meter, of the seal 10 minutes after it entered the water? The SAT. Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #598 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) For each real number r, which of the following points lies on the graph of each equation in the xy-plane for the given system?
(A) 3r 7
(B) 2r 7
(C) 3r 7
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.89; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) 8 x + 7 y = 9 8 x + 7 y = 9 8 x + 7 y = 9 24 x + 21 y = 27 24 x + 21 y = 27 24 x + 21 y = 27
For each real number r r r , which of the following points lies on the graph of each equation in the xy -plane for the given system?
(A) ( r , − 8 r 7 + 9 7 ) \left(r , - \dfrac{8 r}{7} + \dfrac{9}{7}\right) ( r , − 7 8 r + 7 9 )
(B) ( − 8 r 7 + 9 7 , r ) \left(- \dfrac{8 r}{7} + \dfrac{9}{7} , r\right) ( − 7 8 r + 7 9 , r )
(C) ( − 8 r 7 + 9 , 8 r 7 + 27 ) \left(- \dfrac{8 r}{7} + 9 , \dfrac{8 r}{7} + 27\right) ( − 7 8 r + 9 , 7 8 r + 27 )
(D) ( r 3 + 9 , − r 3 + 27 ) \left(\dfrac{r}{3} + 9 , - \dfrac{r}{3} + 27\right) ( 3 r + 9 , − 3 r + 27 )
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>8</mn><mi>x</mi><mo>+</mo><mn>7</mn><mi>y</mi><mo>=</mo><mn>9</mn></mrow><annotation encoding="application/x-tex">8 x + 7 y = 9</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">8</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">7</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">9</span></span></span></span><br /><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>24</mn><mi>x</mi><mo>+</mo><mn>21</mn><mi>y</mi><mo>=</mo><mn>27</mn></mrow><annotation encoding="application/x-tex">24 x + 21 y = 27</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">24</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">21</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">27</span></span></span></span></p>
<p style="text-align: left;">For each real number <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi></mrow><annotation encoding="application/x-tex">r</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span></span></span></span>, which of the following points lies on the graph of each equation in the <em>xy</em>-plane for the given system?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #594 · Full test · math · type: grid_inBank-match candidate available
Currently stored (rendered) The regular price of a shirt at a store is$ 11.70. The sale price of the shirt is8 0% less than the regular price, and the sale price is3 0% greater than the store’s cost for the shirt. What was the store’s cost, in dollars, for the shirt? (Disregard the $ sign when entering your answer. For example, if your answer is $4.97, enter 4.97)
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.95; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The regular price of a shirt at a store is $ 11.70 \$ 11.70 $11.70 . The sale price of the shirt is 80 % 80 \% 80% less than the regular price, and the sale price is 30 % 30 \% 30% greater than the store's cost for the shirt. What was the store’s cost, in dollars, for the shirt? (Disregard the $ \$ $ sign when entering your answer. For example, if your answer is $ 4.97 \$ 4.97 $4.97 , enter 4.97 4.97 4.97 )
Suggested correct answer: 1.8 or 9/5 mismatches stored answer "1 8" -- double check
Verified stem text <p style="text-align: left;">The regular price of a shirt at a store is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>11.70</mn></mrow><annotation encoding="application/x-tex">\$ 11.70</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$11.70</span></span></span></span>. The sale price of the shirt is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>80</mn><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">80 \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">80%</span></span></span></span> less than the regular price, and the sale price is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>30</mn><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">30 \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">30%</span></span></span></span> greater than the store's cost for the shirt. What was the store’s cost, in dollars, for the shirt? (Disregard the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi></mrow><annotation encoding="application/x-tex">\$</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$</span></span></span></span> sign when entering your answer. For example, if your answer is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>4.97</mn></mrow><annotation encoding="application/x-tex">\$ 4.97</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$4.97</span></span></span></span>, enter <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>4.97</mn></mrow><annotation encoding="application/x-tex">4.97</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">4.97</span></span></span></span>)</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #592 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The dot plots represent the distributions of values in data sets A and B. Which of the following statements must be true? I. The median of data set A is equal to the median of data set B. II. The standard deviation of data set A is equal to the standard deviation of data set B.
(A) I only
(B) II only
(C) I and II
(D) Neither I nor II
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.75
Bank-match candidate (unverified) The dot plots represent the distributions of values in data sets A and B.
For the dot plot titled Data Set A:
The number line ranges from 10 to 16 in increments of 1.
The data for the dot plot are as follows:
10: 1 dot
11: 4 dots
12: 2 dots
13: 3 dots
14: 2 dots
15: 4 dots
16: 1 dot
For the dot plot titled Data Set B:
The number line ranges from 10 to 16 in increments of 1.
The data for the dot plot are as follows:
10: 2 dots
11: 4 dots
12: 2 dots
13: 1 dot
14: 2 dots
15: 4 dots
16: 2 dots
Which of the following statements must be true?
The median of data set A is equal to the median of data set B.
The standard deviation of data set A is equal to the standard deviation of data set B.
Suggested correct answer: A
Verified stem text <p style="text-align: left;">The dot plots represent the distributions of values in data sets A and B.</p>
<p style="text-align: center;"></p><svg xmlns="http://www.w3.org/2000/svg" width="384.28" height="142.316" viewBox="0 0 384.28 142.316" role="img" aria-label="2 dot plots titled Data Set A and Data Set B. 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d="M325.848,79.056a3.78,3.78,0,1,1-3.779-3.78A3.778,3.778,0,0,1,325.848,79.056Z"></path><path d="M325.848,65.2a3.78,3.78,0,1,1-3.779-3.78A3.78,3.78,0,0,1,325.848,65.2Z"></path><path d="M299.007,79.056a3.78,3.78,0,1,1-3.778-3.78A3.778,3.778,0,0,1,299.007,79.056Z"></path><path d="M272.163,79.056a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,272.163,79.056Z"></path><path d="M272.163,65.2a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,272.163,65.2Z"></path><path d="M245.319,79.056a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,245.319,79.056Z"></path><path d="M245.319,65.2a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,245.319,65.2Z"></path><path d="M245.319,51.339a3.78,3.78,0,1,1-3.778-3.78A3.776,3.776,0,0,1,245.319,51.339Z"></path><path d="M245.319,37.478a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,245.319,37.478Z"></path><path d="M352.688,79.056a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,352.688,79.056Z"></path><path d="M352.688,65.2a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,352.688,65.2Z"></path><path d="M352.688,51.339a3.78,3.78,0,1,1-3.778-3.78A3.776,3.776,0,0,1,352.688,51.339Z"></path><path d="M352.688,37.478a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,352.688,37.478Z"></path><path d="M218.479,79.056a3.78,3.78,0,1,1-3.778-3.78A3.778,3.778,0,0,1,218.479,79.056Z"></path><path d="M218.479,65.2a3.78,3.78,0,1,1-3.778-3.78A3.78,3.78,0,0,1,218.479,65.2Z"></path><path d="M379.059,79.056a3.78,3.78,0,1,1-3.778-3.78A3.777,3.777,0,0,1,379.059,79.056Z"></path><path d="M379.059,65.2a3.78,3.78,0,1,1-3.778-3.78A3.779,3.779,0,0,1,379.059,65.2Z"></path></g></svg><div role="region" aria-label="Long description for 2 dot plots titled Data Set A and Data Set B" class="sr-only"><ul>
<li>For the dot plot titled Data Set A:
<ul>
<li>The number line ranges from 10 to 16 in increments of 1.</li>
<li>The data for the dot plot are as follows:
<ul>
<li>10: 1 dot</li>
<li>11: 4 dots</li>
<li>12: 2 dots</li>
<li>13: 3 dots</li>
<li>14: 2 dots</li>
<li>15: 4 dots</li>
<li>16: 1 dot</li>
</ul>
</li>
</ul>
</li>
<li>For the dot plot titled Data Set B:
<ul>
<li>The number line ranges from 10 to 16 in increments of 1.</li>
<li>The data for the dot plot are as follows:
<ul>
<li>10: 2 dots</li>
<li>11: 4 dots</li>
<li>12: 2 dots</li>
<li>13: 1 dot</li>
<li>14: 2 dots</li>
<li>15: 4 dots</li>
<li>16: 2 dots</li>
</ul>
</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">Which of the following statements must be true?</p>
<ol style="list-style-type: upper-roman;">
<li style="text-align: left;">The median of data set A is equal to the median of data set B.</li>
<li style="text-align: left;">The standard deviation of data set A is equal to the standard deviation of data set B.</li>
</ol> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #591 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #590 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - A certain township consists of a 5-hectare industrial park and a 24-hectare neighborhood. The total number of trees in the township is 4,529. The equation5 x + 24 y = 4,529 represents this situation. Which of the following is the best interpretation of x in this context?
(A) The average number of trees per hectare in the industrial park
(B) B) The average number of trees per hectare in the neighborhood
(C) The total number of trees in the industrial park
(D) The total number of trees in the neighborhood
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.78
Bank-match candidate (unverified) A neighborhood consists of a 2 2 2 -hectare park and a 35 35 35 -hectare residential area. The total number of trees in the neighborhood is 3 , 934 3,934 3 , 934 . The equation 2 x + 35 y = 3 , 934 2 x + 35 y = 3,934 2 x + 35 y = 3 , 934 represents this situation. Which of the following is the best interpretation of x in this context?
(A) The average number of trees per hectare in the park
(B) The average number of trees per hectare in the residential area
(C) The total number of trees in the park
(D) The total number of trees in the residential area
Suggested correct answer: A
Verified stem text <p>A neighborhood consists of a <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn></mrow><annotation encoding="application/x-tex">2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2</span></span></span></span>-hectare park and a <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>35</mn></mrow><annotation encoding="application/x-tex">35</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">35</span></span></span></span>-hectare residential area. The total number of trees in the neighborhood is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3</mn><mo separator="true">,</mo><mn>934</mn></mrow><annotation encoding="application/x-tex">3,934</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">3</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">934</span></span></span></span>. The equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn><mi>x</mi><mo>+</mo><mn>35</mn><mi>y</mi><mo>=</mo><mn>3</mn><mo separator="true">,</mo><mn>934</mn></mrow><annotation encoding="application/x-tex">2 x + 35 y = 3,934</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">2</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">35</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">3</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">934</span></span></span></span> represents this situation. Which of the following is the best interpretation of <em>x</em> in this context?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #588 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #587 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #585 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #584 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #582 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #581 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 1 The function f is defined by f ( x) = x− 2. What 10 is the y-intercept of the graph of y = f ( x)in the xy-plane?
(B) 1
(C) 1
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.82
Bank-match candidate (unverified) The function f f f is defined by f ( x ) = 1 10 x − 2 f \left(x\right) = \dfrac{1}{10} x - 2 f ( x ) = 10 1 x − 2 . What is the y -intercept of the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) in the xy -plane?
(A) ( − 2 , 0 ) \left(- 2 , 0\right) ( − 2 , 0 )
(B) ( 0 , − 2 ) \left(0 , - 2\right) ( 0 , − 2 )
(C) ( 0 , 1 10 ) \left(0 , \dfrac{1}{10}\right) ( 0 , 10 1 )
(D) ( 1 10 , 0 ) \left(\dfrac{1}{10} , 0\right) ( 10 1 , 0 )
Suggested correct answer: B
Verified stem text <p>The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span><em> </em>is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>1</mn><mn>10</mn></mfrac></mstyle><mi>x</mi><mo>−</mo><mn>2</mn></mrow><annotation encoding="application/x-tex">f \left(x\right) = \dfrac{1}{10} x - 2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">10</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">1</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2</span></span></span></span>. What is the <em>y</em>-intercept of the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <em>xy</em>-plane?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #578 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #576 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) In the figure, line m is parallel to line n, and line t intersects both lines. What is the value of x ?
(A) 33
(B) 57
(C) 123
(D) 147
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.68; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
In the figure above, lines m m m and n n n are parallel. What is the value of b b b ?
Suggested correct answer: A mismatches stored answer "D" -- double check
Verified stem text <div class="stimulus_reference ">
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<img 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" alt="The figure presents 5 lines labeled j, k, l, m, and n. Lines m and n are horizontal and line m lies above line n. Line j is slanted downward and to the right, and line k is slanted upward and to the right. Lines j, k, and top horizontal line m intersect, forming six angles. The angle below line m and to the left of line k and the angle below line m and to the right of line j are both labeled, a, degrees. Line k intersects the bottom horizontal line n, forming four angles. The angle above line n and to the left of line k is labeled 130 degrees. Line l is vertical and intersects lines m and n on the right side of the figure. Line j, line l, and the bottom horizontal line n intersect, forming six angles. The angle, above line n, to the left of vertical line l, and to the right of line j is labeled b degrees. There is a right angle symbol at an angle formed by horizontal line m and vertical line l." /></div>
</div>
<p class="stem_paragraph ">In the figure above, lines <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>m</mi></mrow><annotation encoding="application/x-tex">m</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">m</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span> are parallel. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #575 · Full test · math · type: mcq
Source PDF page (reference) Question #574 · Full test · math · type: grid_in
Source PDF page (reference) Question #573 · Full test · math · type: grid_inBank-match candidate available
Currently stored (rendered) The perimeter of an equilateral triangle is 852 centimeters. The three vertices of the triangle lie on a circle. The radius of the circle is w 3 centimeters. What is the value of w ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The perimeter of an equilateral triangle is 624 624 624 centimeters. The height of this triangle is k 3 k \sqrt{3} k 3 centimeters, where k k k is a constant. What is the value of k k k ?
Suggested correct answer: 104 mismatches stored answer "2843" -- double check
Verified stem text <p style="text-align: left;">The perimeter of an equilateral triangle is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>624</mn></mrow><annotation encoding="application/x-tex">624</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">624</span></span></span></span> centimeters. The height of this triangle is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi><msqrt><mn>3</mn></msqrt></mrow><annotation encoding="application/x-tex">k \sqrt{3}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1328em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">3</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1328em;"><span></span></span></span></span></span></span></span></span> centimeters, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span> is a constant. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #565 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #562 · Full test · math · type: mcq
Currently stored (rendered) The graph of y = f (x ) function f is defined by and a, b, c, and d are constants. For how many values of x does f ( x ) = 0 ?
(A) One
(B) Two
(C) Three
(D) Four 16 The area A, in square centimeters, of a rectangular cutting board can be represented by the expression , where w is the width, in centimeters, of the cutting board. Which expression represents the length, in centimeters, of the cutting board? A) w ( w + 9) B) w C) 9 D) ( w + 9)
Corrected stem text The graph of §IMG§/full-test-images/test-8-math-1-16-inline-0_hi.png§y = f (x ) function f is defined by and a, b, c, and d are constants. For how many values of x does §IMG§/full-test-images/test-8-math-1-16-inline-1_hi.png§f ( x ) = 0 ? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #561 · Full test · math · type: grid_in
Source PDF page (reference) Question #560 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #557 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #554 · Full test · math · type: mcq
Source PDF page (reference) Question #552 · Full test · math · type: grid_inno answer key
Source PDF page (reference) Question #551 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - An analyst collected data on the price of a carton of grape tomatoes at 30 locations selected at random in Utah. The mean price of a carton of grape tomatoes in Utah was estimated to be$ 4.23, with an associated margin of error of$ 0.08. Which of the following is a plausible statement about the mean price of a carton of grape tomatoes for all locations that sell this product in Utah?
(A) It is between and $ 4.31.
(B) It is either less than or greater than$ 4.31.
(C) It is less than .
(D) It is greater than .
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) A sample consisting of 720 720 720 adults who own televisions was selected at random for a study. Based on the sample, it is estimated that 32 % 32 \% 32% of all adults who own televisions use their televisions to watch nature shows, with an associated margin of error of 3.41 % 3.41 \% 3.41% . Which of the following is the most plausible conclusion about all adults who own televisions?
(A) More than 35.41 % 35.41 \% 35.41% of all adults who own televisions use their televisions to watch nature shows.
(B) Between 28.59 % 28.59 \% 28.59% and 35.41 % 35.41 \% 35.41% of all adults who own televisions use their televisions to watch nature shows.
(C) Since the sample included adults who own televisions and not just those who use their televisions to watch nature shows, no conclusion can be made.
(D) Since the sample did not include all the people who watch nature shows, no conclusion can be made.
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p>A sample consisting of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>720</mn></mrow><annotation encoding="application/x-tex">720</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">720</span></span></span></span> adults who own televisions was selected at random for a study. Based on the sample, it is estimated that <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>32</mn><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">32 \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">32%</span></span></span></span> of all adults who own televisions use their televisions to watch nature shows, with an associated margin of error of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3.41</mn><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">3.41 \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">3.41%</span></span></span></span>. Which of the following is the most plausible conclusion about all adults who own televisions?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #550 · Full test · math · type: mcq
Source PDF page (reference) Question #549 · Full test · math · type: mcq
Source PDF page (reference) Question #545 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Some sandstone arches in Utah’s Arches National Park have been defaced by tourists’ carvings. • Park rangers can smooth away some carvings using power grinders. • For deep carvings, power grinding is not always feasible because it can greatly alter or damage the rock. • Park rangers can use an infilling technique, which involves filling in carvings with ground sandstone and a bonding agent. • This technique is minimally invasive. The student wants to explain an advantage of the infilling technique. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) To remove carvings from sandstone arches in Utah’s Arches National Park, power grinding is not always feasible.
(B) Filling in carvings with ground sandstone and a bonding agent is less invasive than smoothing them away with a power grinder, which can greatly alter or damage the sandstone arches.
(C) Park rangers can use a power grinding technique to smooth away carvings or fill them in with ground sandstone and a bonding agent.
(D) As methods for removing carvings from sandstone, power grinding and infilling differ in their level of invasiveness.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Some sandstone arches in Utah’s Arches National Park have been defaced by tourists’ carvings.
Park rangers can smooth away some carvings using power grinders.
For deep carvings, power grinding is not always feasible because it can greatly alter or damage the rock.
Park rangers can use an infilling technique, which involves filling in carvings with ground sandstone and a bonding agent.
This technique is minimally invasive.
The student wants to explain an advantage of the infilling technique. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) To remove carvings from sandstone arches in Utah’s Arches National Park, power grinding is not always feasible.
(B) Filling in carvings with ground sandstone and a bonding agent is less invasive than smoothing them away with a power grinder, which can greatly alter or damage the sandstone arches.
(C) Park rangers can use a power grinding technique to smooth away carvings or fill them in with ground sandstone and a bonding agent.
(D) As methods for removing carvings from sandstone, power grinding and infilling differ in their level of invasiveness.
Suggested correct answer: B
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Some sandstone arches in Utah’s Arches National Park have been defaced by tourists’ carvings.</li>
<li>Park rangers can smooth away some carvings using power grinders.</li>
<li>For deep carvings, power grinding is not always feasible because it can greatly alter or damage the rock.</li>
<li>Park rangers can use an infilling technique, which involves filling in carvings with ground sandstone and a bonding agent.</li>
<li>This technique is minimally invasive.</li>
</ul>
<p>The student wants to explain an advantage of the infilling technique. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #544 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Economist Elinor Ostrom’s studies of communities around the world have empirically demonstrated that common pool resources, such as grazing lands, can be sustainably managed by the people who use them (rather than through private entities or centralized governments). _______ Ostrom’s work is a repudiation of the “tragedy of the commons,” the view that individuals will inevitably overexploit a finite shared resource if given unfettered access to it. Which choice completes the text with the most logical transition?
(A) By contrast,
(B) For example,
(C) That said,
(D) As such,
Corrected stem text Economist Elinor Ostrom’s studies of communities around the world have empirically demonstrated that common pool resources, such as grazing lands, can be sustainably managed by the people who use them (rather than through private entities or centralized governments). _______ Ostrom’s work is a repudiation of the “tragedy of the commons,” the view that individuals will inevitably overexploit a finite shared resource if given unfettered access to it. Which choice completes the text with the most logical transition? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #531 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The morphological novelty of echinoderms—marine invertebrates with radial symmetry, usually starlike, around a central point—impedes comparisons with most other animals, in which bilateral symmetry on an anterior-posterior (head to tail) axis through a trunk is typical. Particularly puzzling are sea stars, thought to have evolved a headless layout from a known bilateral origin. Applying genomic knowledge of Saccoglossus kowalevskii acorn worms (close relatives of sea stars, and thus expected to have similar markers for corresponding anatomical regions) to the body patterning genes of Patiria miniata sea stars, Laurent Formery et al. observed activity only in anterior genes across P. miniata’s entire body and some posterior genes limited to the edges, suggesting that _______ Which choice most logically completes the text?
(A) despite the greater prevalence of anterior genes in sea stars’ genetic makeup, posterior genes active at the body’s perimeter are primarily responsible for the starlike layout that distinguishes sea stars’ radial symmetry from that of other echinoderms.
(B) contrary to the belief that they evolved from early ancestors with the bilateral form typical of many other animals, sea stars instead originated with an atypical body layout that was neither bilaterally nor radially symmetrical.
(C) although the two species are closely related, there is only minimal correspondence in the genetic markers for head, tail, and trunk region development in P. miniata sea stars and S. kowalevskii acorn worms.
(D) rather than undergoing changes resulting in the eventual elimination of a head region in their radial body plan, as previously assumed, sea stars’ morphology evolved to completely lack a trunk and consist primarily of a head region.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) Birds of many species ingest foods containing carotenoids, pigmented molecules that are converted into feather coloration. Coloration tends to be especially saturated in male birds’ feathers, and because carotenoids also confer health benefits, the deeply saturated colors generally serve to communicate what is known as an honest signal of a bird’s overall fitness to potential mates. However, ornithologist Allison J. Shultz and others have found that males in several species of the tanager genus Ramphocelus use microstructures in their feathers to manipulate light, creating the appearance of deeper saturation without the birds necessarily having to maintain a carotenoid-rich diet. These findings suggest that ______ blank
Which choice most logically completes the text?
(A) individual male tanagers can engage in honest signaling without relying on carotenoid consumption.
(B) feather microstructures may be less effective than deeply saturated feathers for signaling overall fitness.
(C) scientists have yet to determine why tanagers have a preference for mates with colorful appearances.
(D) a male tanager’s appearance may function as a dishonest signal of the individual’s overall fitness.
Suggested correct answer: D
Verified stem text <p>Birds of many species ingest foods containing carotenoids, pigmented molecules that are converted into feather coloration. Coloration tends to be especially saturated in male birds’ feathers, and because carotenoids also confer health benefits, the deeply saturated colors generally serve to communicate what is known as an honest signal of a bird’s overall fitness to potential mates. However, ornithologist Allison J. Shultz and others have found that males in several species of the tanager genus <em>Ramphocelus</em> use microstructures in their feathers to manipulate light, creating the appearance of deeper saturation without the birds necessarily having to maintain a carotenoid-rich diet. These findings suggest that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #521 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The following text is adapted from Jane Austen’s 1814 novel Mansfield Park. The speaker, Tom, is considering staging a play at home with a group of his friends and family. We mean nothing but a little amusement among ourselves, just to vary the scene, and exercise our powers in something new. We want no audience, no publicity. We may be trusted, I think, in choosing some play most perfectly unexceptionable; and I can conceive no greater harm or danger to any of us in conversing in the elegant written language of some respectable author than in chattering in words of our own. Which choice best states the main purpose of the text?
(A) To offer Tom’s assurance that the play will be inoffensive and involve only a small number of people
(B) To clarify that the play will not be performed in the manner Tom had originally intended
(C) To elaborate on the idea that the people around Tom lack the skills to successfully stage a play
(D) To assert that Tom believes the group performing the play will be able to successfully promote it
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The following text is adapted from Jane Austen’s 1814 novel Mansfield Park . The speaker, Tom, is considering staging a play at home with a group of his friends and family.
We mean nothing but a little amusement among ourselves, just to vary the scene, and exercise our powers in something new. We want no audience, no publicity. We may be trusted, I think, in choosing some play most perfectly unexceptionable; and I can conceive no greater harm or danger to any of us in conversing in the elegant written language of some respectable author than in chattering in words of our own.
Which choice best states the main purpose of the text?
(A) To offer Tom’s assurance that the play will be inoffensive and involve only a small number of people
(B) To clarify that the play will not be performed in the manner Tom had originally intended
(C) To elaborate on the idea that the people around Tom lack the skills to successfully stage a play
(D) To assert that Tom believes the group performing the play will be able to successfully promote it
Suggested correct answer: A
Verified stem text <p>The following text is adapted from Jane Austen’s 1814 novel <em>Mansfield Park</em>. The speaker, Tom, is considering staging a play at home with a group of his friends and family.</p>
<p style="padding-left:1em;">We mean nothing but a little amusement among ourselves, just to vary the scene, and exercise our powers in something new. We want no audience, no publicity. We may be trusted, I think, in choosing some play most perfectly unexceptionable; and I can conceive no greater harm or danger to any of us in conversing in the elegant written language of some respectable author than in chattering in words of our own.</p>
<p>Which choice best states the main purpose of the text? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #520 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The following text is adapted from Gwendolyn
Bennett’s 1926 poem “Street Lamps in Early Spring.”
Night wears a garment
All velvet soft, all violet blue...
And over her face she draws a veil
As shimmering fine as floating dew...
And here and there
In the black of her hair
The subtle hands of Night
Move slowly with their gem-starred light.
Which choice best describes the overall structure of
the text?
(A) It presents alternating descriptions of night in a rural area and in a city.
(B) It sketches an image of nightfall, then an image of sunrise.
(C) It makes an extended comparison of night to a human being.
(D) It portrays how night changes from one season of the year to the next.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The following text is adapted from Gwendolyn Bennett’s 1926 poem “Street Lamps in Early Spring.”
Night wears a garment All velvet soft, all violet blue... And over her face she draws a veil As shimmering fine as floating dew... And here and there In the black of her hair The subtle hands of Night Move slowly with their gem-starred light.
Which choice best describes the overall structure of the text?
(A) It presents alternating descriptions of night in a rural area and in a city.
(B) It sketches an image of nightfall, then an image of sunrise.
(C) It makes an extended comparison of night to a human being.
(D) It portrays how night changes from one season of the year to the next.
Suggested correct answer: C
Verified stem text <p>The following text is adapted from Gwendolyn Bennett’s 1926 poem “Street Lamps in Early Spring.” </p>
<p style="padding-left:1em;">Night wears a garment<br />All velvet soft, all violet blue... <br />And over her face she draws a veil<br />As shimmering fine as floating dew... <br />And here and there<br />In the black of her hair<br />The subtle hands of Night<br />Move slowly with their gem-starred light.</p>
<p>Which choice best describes the overall structure of the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #510 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794. • It was the first private turnpike in the United States. • It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania. • It was sixty-two miles long. The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The sixty-two-mile-long Philadelphia and Lancaster Turnpike connected the Pennsylvania cities of Philadelphia and Lancaster.
(B) The Philadelphia and Lancaster Turnpike was the first private turnpike in the United States.
(C) The Philadelphia and Lancaster Turnpike, which connected two Pennsylvania cities, was built between 1792 and 1794.
(D) A historic Pennsylvania road, the Philadelphia and Lancaster Turnpike was completed in 1794.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.
It was the first private turnpike in the United States.
It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.
It was sixty-two miles long.
The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The sixty-two-mile-long Philadelphia and Lancaster Turnpike connected the Pennsylvania cities of Philadelphia and Lancaster.
(B) The Philadelphia and Lancaster Turnpike was the first private turnpike in the United States.
(C) The Philadelphia and Lancaster Turnpike, which connected two Pennsylvania cities, was built between 1792 and 1794.
(D) A historic Pennsylvania road, the Philadelphia and Lancaster Turnpike was completed in 1794.
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.</li>
<li>It was the first private turnpike in the United States.</li>
<li>It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.</li>
<li>It was sixty-two miles long.</li>
</ul>
<p>The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #509 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #508 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In 1974, Mexican chemist Mario Molina and US chemist F. Sherwood Rowland discovered that chemicals called CFCs were harmful to the ozone layer. Their research was extremely influential in the fight against CFCs. _______ it laid the foundation for a 1987 treaty that phased out the use of CFCs across the globe. Which choice completes the text with the most logical transition?
(A) Regardless,
(B) Specifically,
(C) However,
(D) Earlier,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) Most of the planets that have been discovered outside our solar system orbit G-type stars, like our Sun. In 2014, ______ blank researchers identified a planet orbiting KELT-9, a B-type star more than twice as massive and nearly twice as hot as the Sun. Called KELT-9b, it is one of the hottest planets ever discovered.
Which choice completes the text with the most logical transition?
Suggested correct answer: B
Verified stem text <p>Most of the planets that have been discovered outside our solar system orbit G-type stars, like our Sun. In 2014, <span>______</span><span class="sr-only">blank</span> researchers identified a planet orbiting KELT-9, a B-type star more than twice as massive and nearly twice as hot as the Sun. Called KELT-9b, it is one of the hottest planets ever discovered.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #501 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Paintings by the renowned twentieth-century US _______ were featured in Artist to Artist, an exhibition at the Smithsonian Art Museum that paired the works of artists whose career trajectories intersected in meaningful ways. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) artists: Thomas Hart Benton and Jackson Pollock,
(B) artists Thomas Hart Benton and Jackson Pollock
(C) artists Thomas Hart Benton, and Jackson Pollock,
(D) artists, Thomas Hart Benton and Jackson Pollock
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In 2018, the innovative works of Congolese sculptor and architect Bodys Isek ______ blank were featured in City Dreams , a solo exhibition at New York’s Museum of Modern Art.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: C mismatches stored answer "B" -- double check
Verified stem text <p>In 2018, the innovative works of Congolese sculptor and architect Bodys Isek <span>______</span><span class="sr-only">blank</span> were featured in <em>City Dreams</em>, a solo exhibition at New York’s Museum of Modern Art.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #496 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In the mountains of Brazil, Barbacenia tomentosa and Barbacenia macrantha—two plants in the Velloziaceae family—establish themselves on soilless, nutrient-poor patches of quartzite rock. Plant ecologists Anna Abrahão and Patricia de Britto Costa used microscopic analysis to determine that the roots of B. tomentosa and B. macrantha, which grow directly into the quartzite, have clusters of fine hairs near the root tip; further analysis indicated that these hairs secrete both malic and citric acids. The researchers hypothesize that the plants depend on dissolving underlying rock with these acids, as the process not only creates channels for continued growth but also releases phosphates that provide the vital nutrient phosphorus. Which finding, if true, would most directly support the researchers’ hypothesis?
(A) Other species in the Velloziaceae family are found in terrains with more soil but have root structures similar to those of B. tomentosa and B. macrantha.
(B) Though B. tomentosa and B. macrantha both secrete citric and malic acids, each species produces the acids in different proportions.
(C) The roots of B. tomentosa and B. macrantha carve new entry points into rocks even when cracks in the surface are readily available.
(D) B. tomentosa and B. macrantha thrive even when transferred to the surfaces of rocks that do not contain phosphates.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In the mountains of Brazil, Barbacenia tomentosa and Barbacenia macrantha —two plants in the Velloziaceae family—establish themselves on soilless, nutrient-poor patches of quartzite rock. Plant ecologists Anna Abrahão and Patricia de Britto Costa used microscopic analysis to determine that the roots of B. tomentosa and B. macrantha , which grow directly into the quartzite, have clusters of fine hairs near the root tip; further analysis indicated that these hairs secrete both malic and citric acids. The researchers hypothesize that the plants depend on dissolving underlying rock with these acids, as the process not only creates channels for continued growth but also releases phosphates that provide the vital nutrient phosphorus.
Which finding, if true, would most directly support the researchers’ hypothesis?
(A) Other species in the Velloziaceae family are found in terrains with more soil but have root structures similar to those of B. tomentosa and B. macrantha .
(B) Though B. tomentosa and B. macrantha both secrete citric and malic acids, each species produces the acids in different proportions.
(C) The roots of B. tomentosa and B. macrantha carve new entry points into rocks even when cracks in the surface are readily available.
(D) B. tomentosa and B. macrantha thrive even when transferred to the surfaces of rocks that do not contain phosphates.
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p>In the mountains of Brazil, <em>Barbacenia tomentosa</em> and <em>Barbacenia macrantha</em>—two plants in the Velloziaceae family—establish themselves on soilless, nutrient-poor patches of quartzite rock. Plant ecologists Anna Abrahão and Patricia de Britto Costa used microscopic analysis to determine that the roots of <em>B. tomentosa </em>and <em>B. macrantha</em>, which grow directly into the quartzite, have<em> </em>clusters of fine hairs near the root tip; further analysis indicated that these hairs secrete both malic and citric acids. The researchers hypothesize that the plants depend on dissolving underlying rock with these acids, as the process not only creates channels for continued growth but also releases phosphates that provide the vital nutrient phosphorus.</p>
<p>Which finding, if true, would most directly support the researchers’ hypothesis?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #495 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Researchers hypothesized that a decline in the population of dusky sharks near the mid-Atlantic coast of North America led to a decline in the population of eastern oysters in the region. Dusky sharks do not typically consume eastern oysters but do consume cownose rays, which are the main predators of the oysters. Which finding, if true, would most directly support the researchers’ hypothesis?
(A) Declines in the regional abundance of dusky sharks’ prey other than cownose rays are associated with regional declines in dusky shark abundance.
(B) Eastern oyster abundance tends to be greater in areas with both dusky sharks and cownose rays than in areas with only dusky sharks.
(C) Consumption of eastern oysters by cownose rays in the region substantially increased before the regional decline in dusky shark abundance began.
(D) Cownose rays have increased in regional abundance as dusky sharks have decreased in regional abundance.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Researchers hypothesized that a decline in the population of dusky sharks near the mid-Atlantic coast of North America led to a decline in the population of eastern oysters in the region. Dusky sharks do not typically consume eastern oysters but do consume cownose rays, which are the main predators of the oysters.
Which finding, if true, would most directly support the researchers’ hypothesis?
(A) Declines in the regional abundance of dusky sharks’ prey other than cownose rays are associated with regional declines in dusky shark abundance.
(B) Eastern oyster abundance tends to be greater in areas with both dusky sharks and cownose rays than in areas with only dusky sharks.
(C) Consumption of eastern oysters by cownose rays in the region substantially increased before the regional decline in dusky shark abundance began.
(D) Cownose rays have increased in regional abundance as dusky sharks have decreased in regional abundance.
Suggested correct answer: D
Verified stem text <p>Researchers hypothesized that a decline in the population of dusky sharks near the mid-Atlantic coast of North America led to a decline in the population of eastern oysters in the region. Dusky sharks do not typically consume eastern oysters but do consume cownose rays, which are the main predators of the oysters.</p>
<p>Which finding, if true, would most directly support the researchers’ hypothesis?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #493 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Housing Starts in the US, January–April 2022 (in thousands)
IMG§/full-test-images/test-8-rw-1-13-inline-1.png§Month Housing starts§ January 1,669 February _______ 1,771 March 1,713 April 1,803
When construction of a single-family house begins, it is called a housing start. In the first four months of 2022, the highest number of housing starts in the United States was in _____ Which choice most effectively uses data from the table to complete the statement?
(A) April.
(B) March.
(C) January.
(D) February.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.43
Bank-match candidate (unverified)
Percent of Residents of City Areas in Favor of Adding More Bike Paths
City Area Percent of area’s residents in favor of adding more bike paths North East 12% North Central 26% North West 46% South West 88% South Central 33%
A city’s Parks and Recreation department is interested in providing residents with more opportunities for bicycling in their neighborhoods. They’re considering adding more bike paths and conducted a survey to understand where demand for more bike paths is highest. The survey indicated the highest level of demand, with 88 percent of the residents interested in adding more bike paths, is in the city’s ______ blank
Which choice most effectively uses data from the table to complete the statement?
Suggested correct answer: A
Verified stem text <p></p><table class="gdr"><p style="text-align: center;">Percent of Residents of City Areas in Favor of Adding More Bike Paths</p><thead><tr><th scope="col" style="text-align: center; vertical-align: bottom;">City Area</th><th scope="col" style="text-align: center; vertical-align: bottom;">Percent of area’s residents in favor of adding more bike paths</th></tr></thead><tbody><tr><th scope="row" style="text-align: left;">North East</th><td style="text-align: center;">12%</td></tr><tr><th scope="row" style="text-align: left;">North Central</th><td style="text-align: center;">26%</td></tr><tr><th scope="row" style="text-align: left;">North West</th><td style="text-align: center;">46%</td></tr><tr><th scope="row" style="text-align: left;">South West</th><td style="text-align: center;">88%</td></tr><tr><th scope="row" style="text-align: left;">South Central</th><td style="text-align: center;">33%</td></tr></tbody></table><p></p>
<p>A city’s Parks and Recreation department is interested in providing residents with more opportunities for bicycling in their neighborhoods. They’re considering adding more bike paths and conducted a survey to understand where demand for more bike paths is highest. The survey indicated the highest level of demand, with 88 percent of the residents interested in adding more bike paths, is in the city’s <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most effectively uses data from the table to complete the statement?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #492 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Depths at Which Four Deep-Sea Fish Species Live
Depth below the Species ocean surface Footballfish 200–1,000 meters Southern stoplight loosejaw 500–2,000 meters Black seadevil 250–2,000 meters Bollons’ rattail 300–800 meters
Some oceanic fish species live very deep underwater. Researchers collected data about the depths at which various species live. Based on the information in the table, at what depth does the southern stoplight loosejaw live?
(A) More than 2,000 meters below the surface
(B) 150 to 400 meters below the surface
(C) 500 to 2,000 meters below the surface
(D) 250 to 500 meters below the surface
Corrected stem text Depths at Which Four Deep-Sea Fish Species Live
§IMG§/full-test-images/test-8-rw-1-12-inline-0.png§Depth below the §U§Species ocean surface§ §U§Footballfish 200–1,000 meters§ §U§Southern stoplight loosejaw 500–2,000 meters§ §U§Black seadevil 250–2,000 meters§ §U§Bollons’ rattail 300–800 meters§
Some oceanic fish species live very deep underwater. Researchers collected data about the depths at which various species live. Based on the information in the table, at what depth does the southern stoplight loosejaw live? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #480 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #475 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #472 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - The function h estimates an object’s height, in feet, above the ground t seconds after the object is dropped, where b is a constant. The function estimates that the object is 3,364 feet above the ground when it is dropped att = 0. Approximately how many seconds after being dropped does the function estimate the object will hit the ground?
(A) 7.25
(B) 14.50
(C) 105.13
(D) 210.25
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.50
Bank-match candidate (unverified) A quadratic function models a projectile's height, in meters, above the ground in terms of the time, in seconds, after it was launched. The model estimates that the projectile was launched from an initial height of 7 7 7 meters above the ground and reached a maximum height of 51.1 51.1 51.1 meters above the ground 3 3 3 seconds after the launch. How many seconds after the launch does the model estimate that the projectile will return to a height of 7 7 7 meters?
Suggested correct answer: B
Verified stem text <p style="text-align: left;">A quadratic function models a projectile's height, in meters, above the ground in terms of the time, in seconds, after it was launched. The model estimates that the projectile was launched from an initial height of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>7</mn></mrow><annotation encoding="application/x-tex">7</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">7</span></span></span></span> meters above the ground and reached a maximum height of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>51.1</mn></mrow><annotation encoding="application/x-tex">51.1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">51.1</span></span></span></span> meters above the ground <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3</mn></mrow><annotation encoding="application/x-tex">3</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">3</span></span></span></span> seconds after the launch. How many seconds after the launch does the model estimate that the projectile will return to a height of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>7</mn></mrow><annotation encoding="application/x-tex">7</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">7</span></span></span></span> meters?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #471 · Full test · math · type: mcqBank-match candidate available
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Source PDF page (reference) Question #452 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The cost of renting a carpet cleaner is $52 for the first day and $26 for each additional day. Which of the following functions gives the costC (d ), in dollars, of renting the carpet cleaner for d days, where d is a positive integer?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.70; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The cost of renting a backhoe for up to 10 10 10 days is $ 270 \$ 270 $270 for the first day and $ 135 \$ 135 $135 for each additional day. Which of the following equations gives the cost y y y , in dollars, of renting the backhoe for x x x days, where x x x is a positive integer and x ≤ 10 x \leq 10 x ≤ 10 ?
(A) y = 270 x − 135 y = 270 x - 135 y = 270 x − 135
(B) y = 270 x + 135 y = 270 x + 135 y = 270 x + 135
(C) y = 135 x + 270 y = 135 x + 270 y = 135 x + 270
(D) y = 135 x + 135 y = 135 x + 135 y = 135 x + 135
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: left;">The cost of renting a backhoe for up to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>10</mn></mrow><annotation encoding="application/x-tex">10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span> days is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>270</mn></mrow><annotation encoding="application/x-tex">\$ 270</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$270</span></span></span></span> for the first day and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>135</mn></mrow><annotation encoding="application/x-tex">\$ 135</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$135</span></span></span></span> for each additional day. Which of the following equations gives the cost <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>, in dollars, of renting the backhoe for <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> days, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> is a positive integer and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>≤</mo><mn>10</mn></mrow><annotation encoding="application/x-tex">x \leq 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7719em;vertical-align:-0.136em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">≤</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #451 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #450 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #448 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Points Q and R lie on a circle with center P. The radius of this circle is 9 inches. Triangle PQR has a perimeter of 31 inches. What is the length, in inches, ofQR ?
(B) 13
(D) 9
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.55
Bank-match candidate (unverified) An isosceles right triangle has a perimeter of 94 + 94 2 94 + 94 \sqrt{2} 94 + 94 2 inches. What is the length, in inches, of one leg of this triangle?
Suggested correct answer: B
Verified stem text <p style="text-align: left;">An isosceles right triangle has a perimeter of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>94</mn><mo>+</mo><mn>94</mn><msqrt><mn>2</mn></msqrt></mrow><annotation encoding="application/x-tex">94 + 94 \sqrt{2}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">94</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1328em;"></span><span class="mord">94</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">2</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1328em;"><span></span></span></span></span></span></span></span></span> inches. What is the length, in inches, of one leg of this triangle?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #445 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The given equation relates the variables n, t, and w, wheren > 0,t > 0, andw > t. Which expression is equivalent to n ?
(B) w −t
(C) 6tw
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59
Bank-match candidate (unverified) 6 r = 7 s + t 6 r = 7 s + t 6 r = 7 s + t
The given equation relates the variables r r r , s s s , and t t t . Which equation correctly expresses s s s in terms of r r r and t t t ?
(A) s = 42 r − t s = 42 r - t s = 42 r − t
(B) s = 7 ( 6 r − t ) s = 7 \left(6 r - t\right) s = 7 ( 6 r − t )
(C) s = 6 7 r − t s = \dfrac{6}{7} r - t s = 7 6 r − t
(D) s = 6 r − t 7 s = \dfrac{6 r - t}{7} s = 7 6 r − t
Suggested correct answer: D
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><mi>r</mi><mo>=</mo><mn>7</mn><mi>s</mi><mo>+</mo><mi>t</mi></mrow><annotation encoding="application/x-tex">6 r = 7 s + t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">6</span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">7</span><span class="mord mathnormal">s</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span></p>
<p style="text-align: left;">The given equation relates the variables <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi></mrow><annotation encoding="application/x-tex">r</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>s</mi></mrow><annotation encoding="application/x-tex">s</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">s</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span>. Which equation correctly expresses <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>s</mi></mrow><annotation encoding="application/x-tex">s</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">s</span></span></span></span> in terms of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi></mrow><annotation encoding="application/x-tex">r</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #443 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #442 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #441 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - -plane has the equation . Which of the following gives the center of the circle and its radius?
(A) The center is at and the radius is 8.
(B) The center is at and the radius is 8.
(C) The center is at and the radius is 64.
(D) The center is at and the radius is 64.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.64; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In the x y xy x y -plane, a circle with radius 5 has center ( − 8 , 6 ) \left(-8, 6\right) ( − 8 , 6 ) . Which of the following is an equation of the circle?
(A)
( x − 8 ) 2 + ( y + 6 ) 2 = 25 \left(x - 8\right)^2 + \left(y + 6\right)^2 = 25 ( x − 8 ) 2 + ( y + 6 ) 2 = 25
(B)
( x + 8 ) 2 + ( y − 6 ) 2 = 25 \left(x + 8\right)^2 + \left(y - 6\right)^2 = 25 ( x + 8 ) 2 + ( y − 6 ) 2 = 25
(C)
( x − 8 ) 2 + ( y + 6 ) 2 = 5 \left(x - 8\right)^2 + \left(y + 6\right)^2 = 5 ( x − 8 ) 2 + ( y + 6 ) 2 = 5
(D)
( x + 8 ) 2 + ( y − 6 ) 2 = 5 \left(x + 8\right)^2 + \left(y - 6\right)^2 = 5 ( x + 8 ) 2 + ( y − 6 ) 2 = 5
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p class="stem_paragraph ">In the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane, a circle with radius 5 has center <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mo>−</mo><mn>8</mn><mo separator="true">,</mo><mn>6</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(-8, 6\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">−</span><span class="mord">8</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">6</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span></span>. Which of the following is an equation of the circle?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #439 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #438 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #437 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #436 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #435 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Triangles EFG and JKL are congruent, where E, F, and G correspond to J, K, and L, respectively. The measure of angle E is45° and the measure of angle F is20° . What is the measure of angle J ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60
Bank-match candidate (unverified) Triangles A B C A B C A B C and D E F D E F D E F are congruent, where A A A corresponds to D D D , and B B B and E E E are right angles. The measure of angle A A A is 18 ∘ 18^\circ 1 8 ∘ . What is the measure of angle F F F ?
Suggested correct answer: B
Verified stem text <p style="text-align: left;">Triangles <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi><mi>B</mi><mi>C</mi></mrow><annotation encoding="application/x-tex">A B C</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span><span class="mord mathnormal" style="margin-right:0.0715em;">C</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>D</mi><mi>E</mi><mi>F</mi></mrow><annotation encoding="application/x-tex">D E F</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span> are congruent, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi></mrow><annotation encoding="application/x-tex">A</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span></span></span></span> corresponds to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>D</mi></mrow><annotation encoding="application/x-tex">D</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">D</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>B</mi></mrow><annotation encoding="application/x-tex">B</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0502em;">B</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>E</mi></mrow><annotation encoding="application/x-tex">E</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span></span></span></span> are right angles. The measure of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>A</mi></mrow><annotation encoding="application/x-tex">A</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal">A</span></span></span></span> is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mn>18</mn><mo>∘</mo></msup></mrow><annotation encoding="application/x-tex">18^\circ</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6741em;"></span><span class="mord">1</span><span class="mord"><span class="mord">8</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6741em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mbin mtight">∘</span></span></span></span></span></span></span></span></span></span></span>. What is the measure of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>F</mi></mrow><annotation encoding="application/x-tex">F</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">F</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #434 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The graph shown gives the estimated value, in dollars, of a tablet as a function of the number of months since it was purchased. What is the best interpretation of the y-intercept of the graph in this context?
(A) A) The estimated value of the tablet was $225 when it was purchased.
(B) The estimated value of the tablet 24 months after it was purchased was $225.
(C) The estimated value of the tablet had decreased by $225 in the 24 months after it was purchased.
(D) The estimated value of the tablet decreased by approximately 2.25% each year after it was purchased.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.51
Bank-match candidate (unverified) The equation E ( t ) = 5 ( 1.8 ) t E \left(t\right) = 5 \left(1.8\right)^{t} E ( t ) = 5 ( 1.8 ) t gives the estimated number of employees at a restaurant, where t t t is the number of years since the restaurant opened. Which of the following is the best interpretation of the number 5 5 5 in this context?
(A) The estimated number of employees when the restaurant opened
(B) The increase in the estimated number of employees each year
(C) The number of years the restaurant has been open
(D) The percent increase in the estimated number of employees each year
Suggested correct answer: A
Verified stem text <p style="text-align: left;">The equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>E</mi><mrow><mo fence="true">(</mo><mi>t</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>5</mn><msup><mrow><mo fence="true">(</mo><mn>1.8</mn><mo fence="true">)</mo></mrow><mi>t</mi></msup></mrow><annotation encoding="application/x-tex">E \left(t\right) = 5 \left(1.8\right)^{t}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">t</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1.1835em;vertical-align:-0.25em;"></span><span class="mord">5</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">1.8</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.9335em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">t</span></span></span></span></span></span></span></span></span></span></span></span> gives the estimated number of employees at a restaurant, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> is the number of years since the restaurant opened. Which of the following is the best interpretation of the number <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>5</mn></mrow><annotation encoding="application/x-tex">5</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">5</span></span></span></span> in this context?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #433 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #429 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #427 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 1 The scatterplot shows the temperature, in degrees Fahrenheit( °F), and the distance above sea level, in feet, measured at 6 locations on Mount Jefferson. A line of best fit is also shown. At a distance of 4,000 feet above sea level, what is the temperature, in°F , predicted by the line of best fit?
(A) 47
(B) 35
(C) 25
(D) 0
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62
Bank-match candidate (unverified)
The scatterplot above shows the high temperature on a certain day and the elevation of 8 different locations in the Lake Tahoe Basin. A line of best fit for the data is also shown. What temperature is predicted by the line of best fit for a location in the Lake Tahoe Basin with an elevation of 8,500 feet?
Suggested correct answer: B
Verified stem text <p><img 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" alt="The figure presents a scatterplot titled “Temperature and Elevation.” The horizontal axis is labeled “Elevation, in feet,” and the numbers 6,000 through 9,000, in increments of 500, are indicated. The vertical axis is labeled “Temperature, in degrees Fahrenheit,” and the integers 37 through 45 are indicated. There are 8 data points. The data points begin a little below, and to the right of the top of the vertical axis, then trend downward and to the right. A line of best fit is drawn. The data represented by the 8 data points are as follows. Note that all values are approximate. Point 1. 6,350 feet, 42 point 9 degrees Fahrenheit. Point 2. 6,750 feet, 43 point 8 degrees Fahrenheit. Point 3. 6,750 feet, 42 degrees Fahrenheit. Point 4. 7,500 feet, 42 point 2 degrees Fahrenheit. Point 5. 8,000 feet, 40 point 5 degrees Fahrenheit. Point 6. 8,000 feet, 40 degrees Fahrenheit. Point 7. 8,800 feet, 38 point 6 degrees Fahrenheit. Point 8. 8,800 feet, 37 point 6 degrees Fahrenheit. The line of best fit passes through the data point representing 7,500 feet comma 41 point 1 degrees Fahrenheit, and the data point representing 8,500 feet comma 39 degrees Fahrenheit" /></p><p class="stem_paragraph ">The scatterplot above shows the high temperature on a certain day and the elevation of 8 different locations in the Lake Tahoe Basin. A line of best fit for the data is also shown. What temperature is predicted by the line of best fit for a location in the Lake Tahoe Basin with an elevation of 8,500 feet?</p><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #426 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Chiura Obata was a Japanese American artist who lived in California. • YosemiteFalls is a notable painting by Obata. • It uses a Japanese method of black ink painting calledsumi-e. • This painting was completed in 1930. The student wants to indicate the year YosemiteFalls was completed. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) While living in California, Obata created black ink paintings.
(B) Obata, a Japanese American artist, created a notable painting.
(C) YosemiteFalls was completed in 1930.
(D) Obata used a Japanese painting method called sumi-e.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Gaspar Enriquez is an artist.
He specializes in portraits of Mexican Americans.
A portrait is an artistic representation of a person.
Enriquez completed a painting of the sculptor Luis Jimenez in 2003.
He completed a drawing of the writer Rudolfo Anaya in 2016.
The student wants to emphasize a difference between the two portraits. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The portraits, or artistic representations, of Luis Jimenez and Rudolfo Anaya were both completed by Enriquez in the early 2000s.
(B) Enriquez has completed portraits of numerous Mexican Americans, including sculptor Luis Jimenez and writer Rudolfo Anaya.
(C) While both are by Enriquez, the 2003 portrait of Luis Jimenez is a painting, and the 2016 portrait of Rudolfo Anaya is a drawing.
(D) Luis Jimenez was a Mexican American sculptor, and Rudolfo Anaya was a Mexican American writer.
Suggested correct answer: C
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Gaspar Enriquez is an artist.</li>
<li>He specializes in portraits of Mexican Americans.</li>
<li>A portrait is an artistic representation of a person.</li>
<li>Enriquez completed a painting of the sculptor Luis Jimenez in 2003.</li>
<li>He completed a drawing of the writer Rudolfo Anaya in 2016.</li>
</ul>
<p>The student wants to emphasize a difference between the two portraits. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #425 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Samuel Delany is a US writer known for his science fiction. • Delany’s science fiction novel Babel-17 was published in 1966. • The novel won a Nebula Award in 1967. • The Nebula Awards are given each year to the best works of science fiction published in the US. The student wants to indicate the title of a novel that won a Nebula Award. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Babel-17, by Samuel Delany, won a Nebula Award in 1967.
(B) Samuel Delany published a science fiction novel in 1966.
(C) Samuel Delany is an award-winning US writer known for his science fiction.
(D) One of Samuel Delany’s novels was among the best works of science fiction published in the US.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Samuel Selvon was a Trinidadian author.
The Lonely Londoners is one of his most celebrated novels.
Selvon published the novel in 1956.
It is about a group of men who emigrate from the Caribbean to Great Britain after World War II.
Some of The Lonely Londoners ’ characters also appear in Selvon’s later novel Moses Ascending .
The student wants to introduce Samuel Selvon and his novel The Lonely Londoners to a new audience. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) In 1956, Trinidadian author Samuel Selvon published one of his most celebrated novels, The Lonely Londoners, which is about a group of men who emigrate from the Caribbean to Great Britain after World War II.
(B) Samuel Selvon wrote the novel Moses Ascending after he wrote The Lonely Londoners.
(C) The Lonely Londoners , a celebrated novel that was published in 1956, depicts post–World War II Caribbean migration from the perspective of a Trinidadian author.
(D) Some of the characters who appear in Samuel Selvon’s Moses Ascending also appear in The Lonely Londoners.
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Samuel Selvon was a Trinidadian author.</li>
<li><em>The Lonely Londoners </em>is one of his most celebrated novels.</li>
<li>Selvon published the novel in 1956.</li>
<li>It is about a group of men who emigrate from the Caribbean to Great Britain after World War II.</li>
<li>Some of <em>The Lonely Londoners</em>’ characters also appear in Selvon’s later novel <em>Moses Ascending</em>.</li>
</ul>
<p>The student wants to introduce Samuel Selvon and his novel <em>The Lonely Londoners </em>to a new audience. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #413 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #412 · Full test · rw · type: mcq
Source PDF page (reference) Question #411 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #408 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Early Earth is thought to have been characterized by a stagnant lid tectonic regime, in which the upper lithosphere (the outer rocky layer) was essentially immobile and there was no interaction between the lithosphere and the underlying mantle. Researchers investigated the timing of the transition from a stagnant lid regime to a tectonic plate regime, in which the lithosphere is fractured into dynamic plates that in turn allow lithospheric and mantle material to mix. Examining chemical data from lithospheric and mantle-derived rocks ranging from 285 million to 3.8 billion years old, the researchers dated the transition to 3.2 billion years ago. Which finding, if true, would most directly support the researchers’ conclusion?
(A) Among rocks known to be older than 3.2 billion years, significantly more are mantle derived than lithospheric, but the opposite is true for the rocks younger than 3.2 billion years.
(B) Mantle-derived rocks older than 3.2 billion years show significantly more compositional diversity than lithospheric rocks older than 3.2 billion years do.
(C) There is a positive correlation between the age of lithospheric rocks and their chemical similarity to mantle-derived rocks, and that correlation increases significantly in strength at around 3.2 billion years old.
(D) Mantle-derived rocks younger than 3.2 billion years contain some material that is not found in older mantle-derived rocks but is found in older and contemporaneous lithospheric rocks.
Corrected stem text Early Earth is thought to have been characterized by a stagnant lid tectonic regime, in which the upper lithosphere (the outer rocky layer) was essentially immobile and there was no interaction between the lithosphere and the underlying mantle. Researchers investigated the timing of the transition from a stagnant lid regime to a tectonic plate regime, in which the lithosphere is fractured into dynamic plates that in turn allow lithospheric and mantle material to mix. Examining chemical data from lithospheric and mantle-derived rocks ranging from 285 million to 3.8 billion years old, the researchers dated the transition to 3.2 billion years ago. Which finding, if true, would most directly support the researchers’ conclusion? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #403 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Heveabrasiliensis, a tree in the Amazon rainforest, is the world’s main source of natural rubber. The tree produces a milky substance called latex that is used to make rubber. The bark of Heveabrasiliensis is helpful for the process of making rubber because it has a unique structure that makes it easy to collect latex. A network of tubes in the tree’s inner bark helps the latex to flow out easily when people make small cuts into the bark. What feature of Heveabrasiliensis does the text say is helpful for the process of making rubber?
(A) Its latex produces rubber of an especially high quality.
(B) Its bark has a unique structure that makes it easy to collect latex.
(C) It is able to grow in a wide variety of climates around the world.
(D) It is one of only two trees in the Amazon that produce latex.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.35
Bank-match candidate (unverified) Violins made by Antonio Stradivari and other craftspeople in the sixteenth to eighteenth centuries in Cremona, Italy, produce a sound that is considered superior to that of modern stringed instruments. Some experts have claimed that the type of wood used to create Cremonese violins is responsible for their prized sound, but modern and Cremonese violins are made of the same kinds of wood: maple and spruce. New analysis, however, has revealed unique indications that the wood in the older violins was chemically treated by the makers, leading researchers to suggest that ______ blank
Which choice most logically completes the text?
(A) Cremonese violins probably were not considered superior to other instruments at the time they were made.
(B) the sound quality of Cremonese violins results in part from a method the craftspeople used to alter the wood.
(C) if modern violins were made of a wood other than maple or spruce, they likely would sound as good as Cremonese violins.
(D) the current process of making violins is the same process that was used centuries ago by Cremonese craftspeople.
Suggested correct answer: B
Verified stem text <p>Violins made by Antonio Stradivari and other craftspeople in the sixteenth to eighteenth centuries in Cremona, Italy, produce a sound that is considered superior to that of modern stringed instruments. Some experts have claimed that the type of wood used to create Cremonese violins is responsible for their prized sound, but modern and Cremonese violins are made of the same kinds of wood: maple and spruce. New analysis, however, has revealed unique indications that the wood in the older violins was chemically treated by the makers, leading researchers to suggest that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #398 · Full test · rw · type: mcq
Source PDF page (reference) Question #397 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #396 · Full test · rw · type: mcq
Source PDF page (reference) Question #395 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Painter Alma W. Thomas was fascinated by the colors and shapes found in nature. The flowers and trees in the garden at her home in Washington, DC, _______ her work. For example, Thomas’s use of broken brushstrokes was inspired by the way that light would shine through the leaves of a tree in front of her house. Which choice completes the text with the most logical and precise word or phrase?
(A) restricted
(B) announced
(C) distracted
(D) influenced
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified) In the 1960s, Sam Gilliam, a Black painter from the southern United States, became the first artist to drape painted canvases into flowing shapes. He later explored a different style, ______ blank quilt-like paintings inspired by the patchwork quilting tradition of Black communities in the South.
Which choice completes the text with the most logical and precise word or phrase?
Suggested correct answer: D
Verified stem text <p>In the 1960s, Sam Gilliam, a Black painter from the southern United States, became the first artist to drape painted canvases into flowing shapes. He later explored a different style, <span>______</span><span class="sr-only">blank</span> quilt-like paintings inspired by the patchwork quilting tradition of Black communities in the South.</p>
<p>Which choice completes the text with the most logical and precise word or phrase?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #393 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Researchers in a 2021 study wanted to determine the rate at which 17 languages conveyed both information and syllables. • They calculated the bits of information conveyed per second (the IR, or information rate). • The IR was found to be approximately consistent across the 17 languages (an average of 39 bits per second). • They calculated the number of syllables spoken per second (the SR, or syllable rate). • Spanish had the second-fastest SR (7.7 syllables per second). • Vietnamese had the sixteenth-fastest SR (5.3 syllables per second). The student wants to present an overview of the study’s findings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The 2021 study determined the information rate (IR) of 17 languages in bits of information conveyed per second.
(B) Researchers found that information was conveyed more quickly in Spanish, at 7.7 syllables per second, than in Vietnamese, at 5.3 syllables per second.
(C) Vietnamese had the sixteenth-fastest syllable rate, lower than that of Spanish, which had the second-fastest; however, Spanish had the lower information rate of the two.
(D) Though some of the languages differed in number of syllables spoken per second, all 17 conveyed information at roughly the same rate.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Species belonging to the Orchidaceae (orchid) family can be found in both tropical and temperate environments.
Orchidaceae species diversity has not been well studied in temperate forests, such as those in Oaxaca, Mexico.
Arelee Estefanía Muñoz-Hernández led a study to determine how many different Orchidaceae species are present in the forests of Oaxaca.
Muñoz-Hernández and her team collected orchids each month for a year at a site in Oaxaca.
Seventy-four Orchidaceae species were present at the site.
The student wants to present the study and its findings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) A study led by Arelee Estefanía Muñoz-Hernández identified a total of 74 Orchidaceae species in the temperate forests of Oaxaca, Mexico.
(B) There are orchids in many environments, but there are 74 Orchidaceae species in Oaxaca, Mexico.
(C) Oaxaca, Mexico, is home to temperate forests containing 74 Orchidaceae species.
(D) Arelee Estefanía Muñoz-Hernández and her team wanted to know how many different Orchidaceae species are present in the forests of Oaxaca, Mexico, so they conducted a study to collect orchids.
Suggested correct answer: A mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Species belonging to the Orchidaceae (orchid) family can be found in both tropical and temperate environments.</li>
<li>Orchidaceae species diversity has not been well studied in temperate forests, such as those in Oaxaca, Mexico.</li>
<li>Arelee Estefanía Muñoz-Hernández led a study to determine how many different Orchidaceae species are present in the forests of Oaxaca.</li>
<li>Muñoz-Hernández and her team collected orchids each month for a year at a site in Oaxaca.</li>
<li>Seventy-four Orchidaceae species were present at the site.</li>
</ul>
<p>The student wants to present the study and its findings. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #392 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Political scientist Graham Allison is known for his Thucydides trap theory. • Allison’s theory states that whenever “a rising power is threatening to displace a ruling power,” conflict is likely. • The theory is based on Thucydides’s explanation of the conflict between Athens and Sparta. • Thucydides wrote that “the rise of Athens and the fear this instilled in Sparta” made conflict “inevitable.” • History professor Edmund Stewart recently challenged the historical basis of the theory. • Stewart claimed that Athens was not a rising power and that the rivals experienced a “clash of cultures” instead. The student wants to use a quotation to challenge Thucydides’s explanation of the conflict between Athens and Sparta. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) According to Allison’s Thucydides trap theory, whenever “a rising power is threatening to displace a ruling power,” conflict is likely.
(B) Thucydides wrote that conflict between the two powers was “inevitable,” although Stewart later challenged the historical basis of this claim.
(C) According to Stewart, a “clash of cultures” between Athens and Sparta caused the conflict, not Athens’s rise.
(D) Thucydides explained that conflict was caused by “the rise of Athens and the fear this instilled in Sparta,” but Allison disagreed, seeing the conflict as an example of the Thucydides trap.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Planetary scientists classify asteroids based on their composition.
C-type asteroids are composed primarily of carbon.
They account for roughly 75 percent of known asteroids.
S-type asteroids are primarily made up of silicate minerals.
They account for roughly 17 percent of known asteroids.
The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Planetary scientists classify asteroids into types, two of which are the C-type and the S-type.
(B) Planetary scientists consider an asteroid’s composition (such as whether the asteroid is composed mainly of silicate minerals or carbon) when classifying it.
(C) Roughly 17 percent of known asteroids are classified as S-type asteroids; another percentage is classified as C-type asteroids.
(D) C-type asteroids are mainly composed of carbon, whereas S-type asteroids are primarily made up of silicate minerals.
Suggested correct answer: D mismatches stored answer "C" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Planetary scientists classify asteroids based on their composition.</li>
<li>C-type asteroids are composed primarily of carbon.</li>
<li>They account for roughly 75 percent of known asteroids.</li>
<li>S-type asteroids are primarily made up of silicate minerals.</li>
<li>They account for roughly 17 percent of known asteroids.</li>
</ul>
<p>The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #391 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Musicians around the world have used protest songs to raise awareness about human rights violations. • US folk singer Aunt Molly Jackson released the protest song “Poor Miner’s Farewell” in 1932. • It exposed the unlivable wages and dangerous working conditions coal miners faced in Kentucky during the 1920s and 1930s. • South African singer-songwriter Hugh Masekela released the protest song “Bring Him Back Home” in 1987. • It called on the South African government to free Nelson Mandela, an anti-apartheid leader who’d been unjustly imprisoned. The student wants to contrast the song “Poor Miner’s Farewell” with the song “Bring Him Back Home.” Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The songs “Poor Miner’s Farewell” and “Bring Him Back Home” both raised awareness about human rights violations.
(B) While both are protest songs, “Poor Miner’s Farewell” is about coal miners in Kentucky, whereas “Bring Him Back Home” is about the anti-apartheid leader Nelson Mandela.
(C) Hugh Masekela’s song “Bring Him Back Home,” released in 1987, called on the South African government to free Nelson Mandela.
(D) Released in 1932 by Aunt Molly Jackson, the song “Poor Miner’s Farewell” was a protest against the unlivable wages and dangerous working conditions faced by Kentucky coal miners.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.54
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Some sandstone arches in Utah’s Arches National Park have been defaced by tourists’ carvings.
Park rangers can smooth away some carvings using power grinders.
For deep carvings, power grinding is not always feasible because it can greatly alter or damage the rock.
Park rangers can use an infilling technique, which involves filling in carvings with ground sandstone and a bonding agent.
This technique is minimally invasive.
The student wants to explain an advantage of the infilling technique. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) To remove carvings from sandstone arches in Utah’s Arches National Park, power grinding is not always feasible.
(B) Filling in carvings with ground sandstone and a bonding agent is less invasive than smoothing them away with a power grinder, which can greatly alter or damage the sandstone arches.
(C) Park rangers can use a power grinding technique to smooth away carvings or fill them in with ground sandstone and a bonding agent.
(D) As methods for removing carvings from sandstone, power grinding and infilling differ in their level of invasiveness.
Suggested correct answer: B
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Some sandstone arches in Utah’s Arches National Park have been defaced by tourists’ carvings.</li>
<li>Park rangers can smooth away some carvings using power grinders.</li>
<li>For deep carvings, power grinding is not always feasible because it can greatly alter or damage the rock.</li>
<li>Park rangers can use an infilling technique, which involves filling in carvings with ground sandstone and a bonding agent.</li>
<li>This technique is minimally invasive.</li>
</ul>
<p>The student wants to explain an advantage of the infilling technique. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #390 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The Royal Alcázar of Seville is a historic royal palace in Andalucía, Spain. • The palace is famous for its intricate tilework. • The palace features majolica and arista tiles. • In the majolica style, designs are painted directly on the ceramic tiles. • In the arista style, designs are stamped into the ceramic tiles. The student wants to contrast the two styles of tiles. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Tiles in the majolica and arista styles can be found in the Royal Alcázar of Seville in Andalucía, Spain.
(B) Featuring tiles in the majolica and arista styles, the Royal Alcázar of Seville in Spain is famous for its intricate tilework.
(C) In the arista style, designs are stamped into the ceramic tiles, whereas in the majolica style, the designs are painted directly on them.
(D) Among the famous tilework of the Royal Alcázar of Seville are majolica style tiles, made by painting designs directly on the ceramic tiles.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.
Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.
Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.
At the time, Abele was not formally credited with designing the buildings.
Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.
The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Given that most of the buildings on Duke’s campus feature architectural styles that Abele had studied in Europe, historians believe Abele is the one who designed them.
(B) Though Abele wasn’t formally credited at the time, historians believe he designed most of the buildings on Duke’s campus.
(C) Most of Duke’s campus buildings, which were designed by a firm Abele worked for, were designed in the Gregorian and neo-Gothic architectural styles.
(D) Abele, an architect who studied Gregorian and neo-Gothic architecture in Europe, is believed to have designed most of the buildings on Duke’s campus.
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.</li>
<li>Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.</li>
<li>Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.</li>
<li>At the time, Abele was not formally credited with designing the buildings.</li>
<li>Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.</li>
</ul>
<p>The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #389 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • “Raymond’s Run” is a short story. • It was written by African American author Toni Cade Bambara. • It was first published in her book Gorilla, My Love in 1972. • It is told from a first person perspective. • It takes place in Harlem. The student wants to indicate where the short story takes place. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) “Raymond’s Run” takes place in Harlem.
(B) “Raymond’s Run” was published in Gorilla, My Love.
(C) “Raymond’s Run” is told from a first person perspective.
(D) “Raymond’s Run” was written by Toni Cade Bambara.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.61; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Bharati Mukherjee was an Indian-born author of novels and short stories.
She published the novel The Holder of the World in 1993.
A central character in the novel is a woman living in twentieth-century United States.
Another central character is a woman living in seventeenth-century India.
The student wants to introduce the novel The Holder of the World to an audience already familiar with Bharati Mukherjee. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Bharati Mukherjee’s settings include both twentieth-century United States and seventeenth-century India.
(B) In addition to her novel The Holder of the World, which was published in 1993, Indian-born author Bharati Mukherjee wrote other novels and short stories.
(C) Bharati Mukherjee’s novel The Holder of the World centers around two women, one living in twentieth-century United States and the other in seventeenth-century India.
(D) The Holder of the World was not the only novel written by Indian-born author Bharati Mukherjee.
Suggested correct answer: C mismatches stored answer "A" -- double check
Verified stem text <p> While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Bharati Mukherjee was an Indian-born author of novels and short stories.</li>
<li>She published the novel <em>The Holder of the World</em> in 1993.</li>
<li>A central character in the novel is a woman living in twentieth-century United States.</li>
<li>Another central character is a woman living in seventeenth-century India.</li>
</ul>
<p>The student wants to introduce the novel <em>The Holder of the World </em>to an audience already familiar with Bharati Mukherjee. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #388 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Angana Chaudhuri is a scientist. • Chaudhuri studies sedimentary rocks. • A scientist who studies sedimentary rocks is called a sedimentologist. • Shale, chalk, and sandstone are examples of sedimentary rocks. The student wants to identify what type of scientist Chaudhuri is. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Chalk is a type of sedimentary rock.
(B) Some scientists study shale, chalk, and sandstone.
(C) There are scientists who study sedimentary rocks.
(D) Chaudhuri is a sedimentologist.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Planetary scientists classify asteroids based on their composition.
C-type asteroids are composed primarily of carbon.
They account for roughly 75 percent of known asteroids.
S-type asteroids are primarily made up of silicate minerals.
They account for roughly 17 percent of known asteroids.
The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Planetary scientists classify asteroids into types, two of which are the C-type and the S-type.
(B) Planetary scientists consider an asteroid’s composition (such as whether the asteroid is composed mainly of silicate minerals or carbon) when classifying it.
(C) Roughly 17 percent of known asteroids are classified as S-type asteroids; another percentage is classified as C-type asteroids.
(D) C-type asteroids are mainly composed of carbon, whereas S-type asteroids are primarily made up of silicate minerals.
Suggested correct answer: D
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Planetary scientists classify asteroids based on their composition.</li>
<li>C-type asteroids are composed primarily of carbon.</li>
<li>They account for roughly 75 percent of known asteroids.</li>
<li>S-type asteroids are primarily made up of silicate minerals.</li>
<li>They account for roughly 17 percent of known asteroids.</li>
</ul>
<p>The student wants to emphasize a difference between C-type and S-type asteroids. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #385 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Wanting to celebrate the 100th anniversary of the Alaska Purchase, _______ up with a motto that best captured the state’s unique character. The commission selected “North to the Future,” submitted by Juneau journalist Richard Peter, as its winningentry. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) a contest sponsored by the Alaska Centennial Commission would award $300 to an individual who came
(B) an award of $300 would go to an individual in a contest sponsored by the Alaska Centennial Commission for coming
(C) $300 would be awarded to an individual by the Alaska Centennial Commission in a contest for coming
(D) the Alaska Centennial Commission sponsored a contest that would award $300 to an individual who came
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.48
Bank-match candidate (unverified) Compared to that of alumina glass, ______ blank silica glass atoms are so far apart that they are unable to re-form bonds after being separated.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) silica glass is at a significant disadvantage due to its more dispersed atomic arrangement:
(B) silica glass has a more dispersed atomic arrangement, resulting in a significant disadvantage:
(C) a significant disadvantage of silica glass is that its atomic arrangement is more dispersed:
(D) silica glass’s atomic arrangement is more dispersed, resulting in a significant disadvantage:
Suggested correct answer: D
Verified stem text <p>Compared to that of alumina glass, <span>______</span><span class="sr-only">blank</span> silica glass atoms are so far apart that they are unable to re-form bonds after being separated.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #382 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #377 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Narwhals are shy whales that live in the remote Arctic Ocean. Some of them have a long tusk, like a unicorn horn, with sensitive nerves. Narwhals are known for this tusk, but many actually don’t have one and its purpose is unknown. One group of scientists came up with a possible purpose in 2014. The scientists suggested that the tusk may help narwhals determine when water around them is likely to start freezing and become dangerous for them. Marine biologist Kristin Laidre disagrees with that idea, though. She reasons that if the narwhal’s tusk serves such an important purpose, then it’s most likely that _______ Which choice most logically completes the text?
(A) some narwhals would seek a new habitat.
(B) fewer marine animals would also have tusks.
(C) more narwhals would have a tusk.
(D) narwhals would become less shy over time.
Corrected stem text Narwhals are shy whales that live in the remote Arctic Ocean. Some of them have a long tusk, like a unicorn horn, with sensitive nerves. Narwhals are known for this tusk, but many actually don’t have one and its purpose is unknown. One group of scientists came up with a possible purpose in 2014. The scientists suggested that the tusk may help narwhals determine when water around them is likely to start freezing and become dangerous for them. Marine biologist Kristin Laidre disagrees with that idea, though. She reasons that if the narwhal’s tusk serves such an important purpose, then it’s most likely that _______ Which choice most logically completes the text? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #376 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) A student is researching the Chinese government’s 1992 shift to a market economy that emphasizes trade liberalization. One means of trade liberalization involves expanding from ordinary imports into an emphasis on processing imports, which have two types: processing with assembly (in which a firm obtains raw materials from a foreign trading partner without payment and sells the final goods to that partner, charging for assembly) and processing with inputs (in which a firm expends capital to buy raw materials from a trading partner, processes them into final goods, and sells those goods to whichever trading partner it chooses). The student asserts that while initial efforts at trade liberalization were shaped by Chinese firms’ limited capital, this situation resolved during the 2000s. Which choice best describes data from the graph that support the student’s assertion?
(A) Processing imports with inputs were greater than both ordinary imports and processing imports with assembly in 2006.
(B) From 2000 to 2006, processing imports with inputs rose much more sharply than processing imports with assembly did.
(C) From 2000 to 2006, neither processing imports with inputs nor processing imports with assembly were greater than ordinary imports.
(D) Processing imports with assembly were greater in 2006 than processing imports with inputs in 2000.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.43
Bank-match candidate (unverified) Streams and rivers carry soil and rocks from one location to another. But there is another way for these geological materials to move. Scientists call this process “aeolian transport.” In aeolian transport, winds move small particles of soil or rock over potentially great distances. Geologist Melisa Diaz and her team studied dust in Antarctica to find out if it was moved by aeolian transport. They discovered that the dust matched geological material in Australia. Aeolian transport had carried it from one continent to another, across thousands of miles of open ocean.
Which choice best describes the function of the underlined portion in the text as a whole?
(A) It presents Melisa Diaz’s remarks about difficulties that her team encountered.
(B) It introduces a scientific term that is used in the discussion that follows.
(C) It emphasizes the surprising nature of the findings that are presented.
(D) It explains the difference between two kinds of geological material.
Suggested correct answer: B
Verified stem text <p>Streams and rivers carry soil and rocks from one location to another. But there is another way for these geological materials to move. <span role="region" aria-label="Referenced Content"><u>Scientists call this process “aeolian transport.”</u></span> In aeolian transport, winds move small particles of soil or rock over potentially great distances. Geologist Melisa Diaz and her team studied dust in Antarctica to find out if it was moved by aeolian transport. They discovered that the dust matched geological material in Australia. Aeolian transport had carried it from one continent to another, across thousands of miles of open ocean. </p>
<p>Which choice best describes the function of the underlined portion in the text as a whole?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #374 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Almost all works of fiction contain references to the progression of time, including the time of day when events in a story take place. In a 2020 study, Allen Kim, Charuta Pethe, and Steven Skiena claim that an observable pattern in such references reflects a shift in human behavior prompted by the spread of electric lighting in the late nineteenth century. The researchers drew this conclusion from an analysis of more than 50,000 novels spanning many centuries and cultures, using software to recognize and tally both specific time references—that is, clock phrases, such as 7 a.m. or 2:30 p.m.—and implied ones, such as mentions of meals typically associated with a particular time of day. Which finding from the study, if true, would most directly support the researchers’ conclusion?
(A) Novels published after the year 1800 include the clock phrase 10 a.m. less often than novels published before the year 1800 do.
(B) Novels published after 1880 contain significantly more references to activities occurring after 10 p.m. than do novels from earlier periods.
(C) Among novels published in the nineteenth century, implied time references become steadily more common than clock phrases as publication dates approach 1900.
(D) D) The time references of noon (12 p.m.) and midnight (12 a.m.) are used with roughly the same frequency in the novels. □ urban population growth ■ GDP per capita growth
Corrected stem text Almost all works of fiction contain references to the progression of time, including the time of day when events in a story take place. In a 2020 study, Allen Kim, Charuta Pethe, and Steven Skiena claim that an observable pattern in such references reflects a shift in human behavior prompted by the spread of electric lighting in the late nineteenth century. The researchers drew this conclusion from an analysis of more than 50,000 novels spanning many centuries and cultures, using software to recognize and tally both specific time references—that is, clock phrases, such as 7 a.m. or 2:30 p.m.—and implied ones, such as mentions of meals typically associated with a particular time of day. Which finding from the study, if true, would most directly support the researchers’ conclusion? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #370 · Full test · rw · type: mcqno answer key
Currently stored (rendered) In 2018, scientists discovered an immense aggregation of Muusoctopus robustus (pearl octopuses) along a hydrothermal vent 3,200 meters beneath the ocean’s surface. Water temperatures at this site—named the Octopus Garden—climb as high as11°C , much warmer than the ambient1.6°C typical at this depth. Based on observations made over three years, scientists concluded that temperatures at the site likely confer reproductive benefits and that the site is used exclusively for reproduction—6,000 M. robustus adults, hatchlings, and eggs were observed at the garden, but no juveniles were present. Which statement about M. robustus and the Octopus Garden is best supported by the text?
(A) M. robustus leave the Octopus Garden upon reaching an intermediary stage of development.
(B) The M. robustus population at the Octopus Garden remains stable despite variations in water temperature.
(C) M. robustus nests in the Octopus Garden contain on average fewer but larger eggs than nests at similar ocean depths.
(D) The Octopus Garden provides an ideal feeding ground for M. robustus hatchlings.
Corrected stem text In 2018, scientists discovered an immense aggregation of Muusoctopus robustus (pearl octopuses) along a hydrothermal vent 3,200 meters beneath the ocean’s surface. Water temperatures at this site—named the Octopus Garden—climb as high as11°C§IMG§/full-test-images/test-7-rw-1-10-inline-0_hi.png§, much warmer than the ambient1.6°C§IMG§/full-test-images/test-7-rw-1-10-inline-1_hi.png§typical at this depth. Based on observations made over three years, scientists concluded that temperatures at the site likely confer reproductive benefits and that the site is used exclusively for reproduction—6,000 M. robustus adults, hatchlings, and eggs were observed at the garden, but no juveniles were present. Which statement about M. robustus and the Octopus Garden is best supported by the text? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #368 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The following text is from H.D.’s 1916 poem “Mid-Day.” In the poem, the speaker is on a path in an outdoor setting. A slight wind shakes the seed-pods — my thoughts are spent as the black seeds. My thoughts tear me, I dread their fever. I am scattered in its whirl. I am scattered like the hot shrivelled seeds. Which choice best describes the function of the underlined portion in the text as a whole?
(A) It illustrates a change in the natural environment that the speaker implies is responsible for the growing misgivings described in the text.
(B) It establishes an example of consistency in the natural landscape that the speaker then contrasts with the unpredictability of human emotions.
(C) It presents an observation of an occurrence in the natural world that the speaker then expands on to convey a sense of a turbulent interior state.
(D) It evokes the ordinariness of an event in nature to suggest that the critical self-evaluation the speaker engages in is a common pursuit.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) The following text is from Srimati Svarna Kumari Devi’s 1894 novel The Fatal Garland (translated by A. Christina Albers in 1910). Shakti is walking near a riverbank that she visited frequently during her childhood.
She crossed the woods she knew so well. The trees seemed to extend their branches like welcoming arms. They greeted her as an old friend. Soon she reached the river-side.
Which choice best describes the function of the underlined portion in the text as a whole?
(A) It suggests that Shakti feels uncomfortable near the river.
(B) It indicates that Shakti has lost her sense of direction in the woods.
(C) It emphasizes Shakti’s sense of belonging in the landscape.
(D) It conveys Shakti’s appreciation for her long-term friendships.
Suggested correct answer: C
Verified stem text <p>The following text is from Srimati Svarna Kumari Devi’s 1894 novel <em>The Fatal Garland</em> (translated by A. Christina Albers in 1910). Shakti is walking near a riverbank that she visited frequently during her childhood.</p>
<p>She crossed the woods she knew so well. <span role="region" aria-label="Referenced Content"><u>The trees seemed to extend their branches like welcoming arms.</u></span> They greeted her as an old friend. Soon she reached the river-side.</p>
<p>Which choice best describes the function of the underlined portion in the text as a whole? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #366 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #365 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #360 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #359 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The scatterplot shows the relationship between two variables, x and y, for data set E. A line of best fit is shown. Data set F is created by multiplying the y-coordinate of each data point from data set E by 3.9. Which of the following could be an equation of a line of best fit for data set F?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.69
Bank-match candidate (unverified) The scatterplot shows the relationship between two variables, x x x and y y y . A line of best fit for the data is also shown. Which of the following is closest to the difference between the y y y -coordinate of the data point with x = 1 x = 1 x = 1 and the y y y -value predicted by the line of best fit at x = 1 x = 1 x = 1 ?
Suggested correct answer: A
Verified stem text <p class="stem_paragraph ">The scatterplot shows the relationship between two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>. A line of best fit for the data is also shown. Which of the following is closest to the difference between the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-coordinate of the data point with <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> and the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-value predicted by the line of best fit at <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> ?</p><div class="standalone_image ">
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" alt="The figure presents a scatterplot in the x y plane. The numbers 0 through 6, in increments of 1, are indicated on the x-axis. The numbers 6 through 12, in increments of 1, are indicated on the y-axis. There are 10 data points in the scatterplot. The data points begin at the point with coordinates 0 comma 12, and trend downward and to the right. The coordinates of the data points are as follows. Note that all values are approximate.
Point 1. 0, comma 12.
Point 2. 0 point 8, comma 11.
Point 3. 1, comma 12.
Point 4. 1 point 5, comma 10 point 3.
Point 5. 2, comma 10.
Point 6. 2 point 2, comma 9 point 2.
Point 7. 3, comma 9.
Point 8. 3 point 5, comma 8.
Point 9. 3 point 8, comma 8 point 3.
Point 10. 4, comma 7.
A line of best fit is also drawn. The line slants downward and to the right, passing through the point with approximate coordinates 1 comma 11, and the point with approximate coordinates 4 comma 7 point 5.
" /></div><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #357 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) __t The function f is defined by fx( ) = a x + b, where a and b are constants. In the xy-plane, the graph of passes through the point (−24, 0) , and . Which of the following must be true?
(C) a > b
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.63; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The function h h h is defined by h ( x ) = a x + b h \left(x\right) = a^{x} + b h ( x ) = a x + b , where a a a and b b b are positive constants. The graph of y = h ( x ) y = h \left(x\right) y = h ( x ) in the x y x y x y -plane passes through the points (0 0 0 , 10 10 10 ) and (− 2 -2 − 2 , 325 36 \dfrac{325}{36} 36 325 ). What is the value of a b a b ab ?
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi></mrow><annotation encoding="application/x-tex">h</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">h</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><msup><mi>a</mi><mi>x</mi></msup><mo>+</mo><mi>b</mi></mrow><annotation encoding="application/x-tex">h \left(x\right) = a^{x} + b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7477em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">a</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6644em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">x</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> are positive constants. The graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>h</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = h \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">x y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane passes through the points (<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>0</mn></mrow><annotation encoding="application/x-tex">0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>10</mn></mrow><annotation encoding="application/x-tex">10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span>) and (<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>−</mo><mn>2</mn></mrow><annotation encoding="application/x-tex">-2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord">2</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>325</mn><mn>36</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\dfrac{325}{36}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">36</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">325</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span>). What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><mi>b</mi></mrow><annotation encoding="application/x-tex">a b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">ab</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #356 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The function f is defined by the given equation. The p x {}^{x} x equation can be rewritten as fx( ) = 1 + , 100 where p is a constant. Which of the following is closest to the value of p ?
(A) 16
(B) 21
(C) 46
(D) D) 96 IZ a1npow
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.55; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) x 2 − 2 x − 9 = 0 x^{2} - 2 x - 9 = 0 x 2 − 2 x − 9 = 0
One solution to the given equation can be written as 1 + k 1 + \sqrt{k} 1 + k , where k k k is a constant. What is the value of k k k ?
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mi>x</mi><mn>2</mn></msup><mo>−</mo><mn>2</mn><mi>x</mi><mo>−</mo><mn>9</mn><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">x^{2} - 2 x - 9 = 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">2</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">9</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span></p>
<p style="text-align: left;">One solution to the given equation can be written as <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn><mo>+</mo><msqrt><mi>k</mi></msqrt></mrow><annotation encoding="application/x-tex">1 + \sqrt{k}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">1</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1078em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9322em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span><span style="top:-2.8922em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #355 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) In triangle ABC , angle B is a right angle. The length __t of side AB is 10 37 and the length of side BC is __t 24 37 . What is the length of side AC ? __t
(A) __t
(B) __t
(C) -~t
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.51
Bank-match candidate (unverified) A right triangle has sides of length 2 2 2 \sqrt{2} 2 2 , 6 2 6 \sqrt{2} 6 2 , and 80 \sqrt{80} 80 units. What is the area of the triangle, in square units?
(A) 8 2 + 80 8 \sqrt{2} + \sqrt{80} 8 2 + 80
Suggested correct answer: B
Verified stem text <p style="text-align: left;">A right triangle has sides of length <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn><msqrt><mn>2</mn></msqrt></mrow><annotation encoding="application/x-tex">2 \sqrt{2}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1328em;"></span><span class="mord">2</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">2</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1328em;"><span></span></span></span></span></span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><msqrt><mn>2</mn></msqrt></mrow><annotation encoding="application/x-tex">6 \sqrt{2}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1328em;"></span><span class="mord">6</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">2</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1328em;"><span></span></span></span></span></span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msqrt><mn>80</mn></msqrt></mrow><annotation encoding="application/x-tex">\sqrt{80}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.1328em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9072em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord">80</span></span></span><span style="top:-2.8672em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.1328em;"><span></span></span></span></span></span></span></span></span> units. What is the area of the triangle, in square units?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #351 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #349 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #348 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 4, 10, 18, 4, 4, 5, 6, 5 What is the median of the data set shown?
(A) 4
(B) 5
(C) 7
(D) 14
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58
Bank-match candidate (unverified) 2 2 2 , 9 9 9 , 14 14 14 , 23 23 23 , 32 32 32
What is the mean of the data shown?
Suggested correct answer: B
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn></mrow><annotation encoding="application/x-tex">2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>9</mn></mrow><annotation encoding="application/x-tex">9</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">9</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>14</mn></mrow><annotation encoding="application/x-tex">14</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">14</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>23</mn></mrow><annotation encoding="application/x-tex">23</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">23</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>32</mn></mrow><annotation encoding="application/x-tex">32</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">32</span></span></span></span></p>
<p>What is the mean of the data shown?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #347 · Full test · math · type: grid_inBank-match candidate available
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Source PDF page (reference) Question #338 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - -- The graph of the function f is shown, where y = fx( ). What is the y-intercept of the graph?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The function f f f is defined by f ( x ) = 7 x − 84 f \left(x\right) = 7 x - 84 f ( x ) = 7 x − 84 . What is the x -intercept of the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) in the xy -plane?
(A) ( − 12 , 0 ) \left(- 12 , 0\right) ( − 12 , 0 )
(B) ( − 7 , 0 ) \left(- 7 , 0\right) ( − 7 , 0 )
(C) ( 7 , 0 ) \left(7 , 0\right) ( 7 , 0 )
(D) ( 12 , 0 ) \left(12 , 0\right) ( 12 , 0 )
Suggested correct answer: D mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>7</mn><mi>x</mi><mo>−</mo><mn>84</mn></mrow><annotation encoding="application/x-tex">f \left(x\right) = 7 x - 84</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">7</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">84</span></span></span></span>. What is the <em>x</em>-intercept of the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <em>xy</em>-plane?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #337 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #336 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) On a street with 7 houses, 2 houses are blue. If a house from this street is selected at random, what is the probability of selecting a house that is blue? 1
(A) 2
(B) 5
(C) 7
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In a bag, there are 7 7 7 red, 4 4 4 white, 33 33 33 blue, and 33 33 33 yellow cubes. If one of these cubes is selected at random, what is the probability of selecting a cube that is neither blue nor yellow?
Suggested correct answer: D mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: left;">In a bag, there are <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>7</mn></mrow><annotation encoding="application/x-tex">7</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">7</span></span></span></span> red, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>4</mn></mrow><annotation encoding="application/x-tex">4</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">4</span></span></span></span> white, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>33</mn></mrow><annotation encoding="application/x-tex">33</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">33</span></span></span></span> blue, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>33</mn></mrow><annotation encoding="application/x-tex">33</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">33</span></span></span></span> yellow cubes. If one of these cubes is selected at random, what is the probability of selecting a cube that is <span style="text-decoration: underline;">neither</span> blue <span style="text-decoration: underline;">nor</span> yellow?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #335 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #334 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #331 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) At the time that an article was first featured on the home page of a news website, there were 40 comments on the article. An exponential model estimates that at the end of each hour after the article was first featured on the home page, the number of comments on the article had increased by 190% of the number of comments on the article at the end of the previous hour. Which of the following equations best represents this model, where C is the estimated number of comments on the article t hours after the article was first featured on the home page and t ≤ 4 ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) A model estimates that at the end of each year from 2015 2015 2015 to 2020 2020 2020 , the number of squirrels in a population was 150 % 150 \% 150% more than the number of squirrels in the population at the end of the previous year. The model estimates that at the end of 2016 2016 2016 , there were 180 180 180 squirrels in the population. Which of the following equations represents this model, where n n n is the estimated number of squirrels in the population t t t years after the end of 2015 2015 2015 and t ≤ 5 t \leq 5 t ≤ 5 ?
(A) n = 72 ( 1.5 ) t n = 72 \left(1.5\right)^{t} n = 72 ( 1.5 ) t
(B) n = 72 ( 2.5 ) t n = 72 \left(2.5\right)^{t} n = 72 ( 2.5 ) t
(C) n = 180 ( 1.5 ) t n = 180 \left(1.5\right)^{t} n = 180 ( 1.5 ) t
(D) n = 180 ( 2.5 ) t n = 180 \left(2.5\right)^{t} n = 180 ( 2.5 ) t
Suggested correct answer: B mismatches stored answer "D" -- double check
Verified stem text <p style="text-align: left;">A model estimates that at the end of each year from <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2015</mn></mrow><annotation encoding="application/x-tex">2015</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2015</span></span></span></span> to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2020</mn></mrow><annotation encoding="application/x-tex">2020</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2020</span></span></span></span>, the number of squirrels in a population was <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>150</mn><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">150 \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">150%</span></span></span></span> more than the number of squirrels in the population at the end of the previous year. The model estimates that at the end of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2016</mn></mrow><annotation encoding="application/x-tex">2016</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2016</span></span></span></span>, there were <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>180</mn></mrow><annotation encoding="application/x-tex">180</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">180</span></span></span></span> squirrels in the population. Which of the following equations represents this model, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span> is the estimated number of squirrels in the population <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> years after the end of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2015</mn></mrow><annotation encoding="application/x-tex">2015</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2015</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi><mo>≤</mo><mn>5</mn></mrow><annotation encoding="application/x-tex">t \leq 5</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7719em;vertical-align:-0.136em;"></span><span class="mord mathnormal">t</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">≤</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">5</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #330 · Full test · math · type: mcqBank-match candidate available
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Source PDF page (reference) Question #323 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) P = N ( 19 −C) The given equation relates the positive numbers P, N, and C. Which equation correctly expresses C in termsof P and N ?
(A) 19 −P
(B) P
(C) P
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.80; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) b = 42 c f b = 42 c f b = 42 c f
The given equation relates the positive numbers b b b , c c c , and f f f . Which equation correctly expresses c c c in terms of b b b and f f f ?
(A) c = b 42 f c = \dfrac{b}{42 f} c = 42 f b
(B) c = b − 42 f c = \dfrac{b - 42}{f} c = f b − 42
(D) c = 42 − b − f c = 42 - b - f c = 42 − b − f
Suggested correct answer: A mismatches stored answer "D" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi><mo>=</mo><mn>42</mn><mi>c</mi><mi>f</mi></mrow><annotation encoding="application/x-tex">b = 42 c f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord">42</span><span class="mord mathnormal">c</span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span></p>
<p style="text-align: left;">The given equation relates the positive numbers <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span>, and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>. Which equation correctly expresses <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>c</mi></mrow><annotation encoding="application/x-tex">c</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">c</span></span></span></span> in terms of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #322 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The relationship between two variables, x and y, is linear. For every increase in the value of x by 1, the value of y increases by 8. When the value of x is 2, the value of y is 18. Which equation represents this relationship?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.70; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Two variables, x x x and y y y , are related such that for each increase of 1 1 1 in the value of x x x , the value of y y y increases by a factor of 4 4 4 . When x = 0 x = 0 x = 0 , y = 200 y = 200 y = 200 . Which equation represents this relationship?
(A) y = 4 ( x ) 200 y = 4 \left(x\right)^{200} y = 4 ( x ) 200
(B) y = 4 ( 200 ) x y = 4 \left(200\right)^{x} y = 4 ( 200 ) x
(C) y = 200 ( x ) 4 y = 200 \left(x\right)^{4} y = 200 ( x ) 4
(D) y = 200 ( 4 ) x y = 200 \left(4\right)^{x} y = 200 ( 4 ) x
Suggested correct answer: D mismatches stored answer "C" -- double check
Verified stem text <p style="text-align: left;">Two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>, are related such that for each increase of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn></mrow><annotation encoding="application/x-tex">1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span> in the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span>, the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span> increases by a factor of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>4</mn></mrow><annotation encoding="application/x-tex">4</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">4</span></span></span></span>. When <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">x = 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mn>200</mn></mrow><annotation encoding="application/x-tex">y = 200</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">200</span></span></span></span>. Which equation represents this relationship?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #318 · Full test · math · type: mcq
Source PDF page (reference) Question #317 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #315 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The function P gives the estimated number of marine mammals in a certain area, where t is the number of years since a study began. What is the best interpretation of P (0) = 1,800in this context?
(A) The estimated number of marine mammals in the area was 102 when the study began.
(B) The estimated number of marine mammals in the area was 1,800 when the study began.
(C) The estimated number of marine mammals in the area increased by 102 each year during the study.
(D) The estimated number of marine mammals in the area increased by 1,800 each year during the study.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The equation E ( t ) = 5 ( 1.8 ) t E \left(t\right) = 5 \left(1.8\right)^{t} E ( t ) = 5 ( 1.8 ) t gives the estimated number of employees at a restaurant, where t t t is the number of years since the restaurant opened. Which of the following is the best interpretation of the number 5 5 5 in this context?
(A) The estimated number of employees when the restaurant opened
(B) The increase in the estimated number of employees each year
(C) The number of years the restaurant has been open
(D) The percent increase in the estimated number of employees each year
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: left;">The equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>E</mi><mrow><mo fence="true">(</mo><mi>t</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>5</mn><msup><mrow><mo fence="true">(</mo><mn>1.8</mn><mo fence="true">)</mo></mrow><mi>t</mi></msup></mrow><annotation encoding="application/x-tex">E \left(t\right) = 5 \left(1.8\right)^{t}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">E</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">t</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1.1835em;vertical-align:-0.25em;"></span><span class="mord">5</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">1.8</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.9335em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">t</span></span></span></span></span></span></span></span></span></span></span></span> gives the estimated number of employees at a restaurant, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> is the number of years since the restaurant opened. Which of the following is the best interpretation of the number <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>5</mn></mrow><annotation encoding="application/x-tex">5</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">5</span></span></span></span> in this context?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #311 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) An object was launched upward from a platform. The graph shown models the height above ground, y, in meters, of the object x seconds after it was launched. For which of the following intervals of time was the height of the object increasing for the entireinterval?
(A) From to x = 2
(B) From to x = 4
(C) From to x = 3
(D) From to x = 4
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) An object is kicked from a platform. The equation h = − 4.9 t 2 + 7 t + 9 h = - 4.9 t^{2} + 7 t + 9 h = − 4.9 t 2 + 7 t + 9 represents this situation, where h h h is the height of the object above the ground, in meters, t t t seconds after it is kicked. Which number represents the height, in meters, from which the object was kicked?
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: left;">An object is kicked from a platform. The equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi><mo>=</mo><mo>−</mo><mn>4.9</mn><msup><mi>t</mi><mn>2</mn></msup><mo>+</mo><mn>7</mn><mi>t</mi><mo>+</mo><mn>9</mn></mrow><annotation encoding="application/x-tex">h = - 4.9 t^{2} + 7 t + 9</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord">4.9</span><span class="mord"><span class="mord mathnormal">t</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">7</span><span class="mord mathnormal">t</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">9</span></span></span></span> represents this situation, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi></mrow><annotation encoding="application/x-tex">h</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">h</span></span></span></span> is the height of the object above the ground, in meters, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> seconds after it is kicked. Which number represents the height, in meters, from which the object was kicked?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #309 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #308 · Full test · math · type: mcq
Currently stored (rendered) the data?
(A) B) y 5,000 4,000 3,000 2,000 1,000
(C) D) y 5,000 4,000 3,000 2,000 1,000 3 4 5 6 7X {}^{X} X 4 5 6 7 Which of the following graphs shows the most appropriate model for
Corrected stem text the data? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #307 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #306 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The US government classifies sensitive information according to the degree to which disclosure could affect the nation’s security. • Information that could cause “damage” to national security is classified as Confidential. • Information that could cause “serious damage” to national security is classified as Secret. • Most routine diplomatic correspondence, if disclosed, could cause damage but not serious damage to national security. • Diplomatic correspondence includes communication with both allies and adversaries. The student wants to indicate which category most routine diplomatic correspondence belongs in, based on how sensitive information is classified. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) According to the US government, which classifies such sensitive information as routine diplomatic correspondence, Confidential information could damage national security if disclosed.
(B) Most routine diplomatic correspondence is classified according to the degree to which disclosure could affect the nation’s security.
(C) Having the potential to damage national security if disclosed, most routine diplomatic correspondence is classified as Confidential.
(D) If disclosed, communication with both allies and adversaries could affect the nation’s security.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.
Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.
Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.
At the time, Abele was not formally credited with designing the buildings.
Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.
The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Given that most of the buildings on Duke’s campus feature architectural styles that Abele had studied in Europe, historians believe Abele is the one who designed them.
(B) Though Abele wasn’t formally credited at the time, historians believe he designed most of the buildings on Duke’s campus.
(C) Most of Duke’s campus buildings, which were designed by a firm Abele worked for, were designed in the Gregorian and neo-Gothic architectural styles.
(D) Abele, an architect who studied Gregorian and neo-Gothic architecture in Europe, is believed to have designed most of the buildings on Duke’s campus.
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.</li>
<li>Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.</li>
<li>Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.</li>
<li>At the time, Abele was not formally credited with designing the buildings.</li>
<li>Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.</li>
</ul>
<p>The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #305 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Doña María do Carmo Bandeira was a Brazilian botanist. • Between 1924 and 1941, she collected approximately 800 botanical samples. • She collected a sample of Polytrichum juniperinum from Serra de Itatiaia in Mauá in February of 1925. • She collected a sample of Sphagnum gracilescen from Ponte do Inferno in Corcovado in March of 1925. • Polytrichum juniperinum and Sphagnum gracilescen are both species of moss. The student wants to emphasize the sample collected from Serra de Itatiaia. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Doña María do Carmo Bandeira was a botanist notable for collecting approximately 800 botanical samples between 1924 and 1941.
(B) Among the many botanical samples Doña María do Carmo Bandeira collected was Polytrichum juniperinum, a species of moss she collected from Serra de Itatiaia in 1925.
(C) Between 1924 and 1941, Doña María do Carmo Bandeira collected many botanical samples, such as Polytrichum juniperinum from Serra de Itatiaia and Sphagnum gracilescen from Ponte do Inferno.
(D) Between 1924 and 1941, Doña María do Carmo Bandeira collected samples of Polytrichum juniperinum and Sphagnum gracilescen, both species of moss.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.
It was the first private turnpike in the United States.
It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.
It was sixty-two miles long.
The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The sixty-two-mile-long Philadelphia and Lancaster Turnpike connected the Pennsylvania cities of Philadelphia and Lancaster.
(B) The Philadelphia and Lancaster Turnpike was the first private turnpike in the United States.
(C) The Philadelphia and Lancaster Turnpike, which connected two Pennsylvania cities, was built between 1792 and 1794.
(D) A historic Pennsylvania road, the Philadelphia and Lancaster Turnpike was completed in 1794.
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>The Philadelphia and Lancaster Turnpike was a road built between 1792 and 1794.</li>
<li>It was the first private turnpike in the United States.</li>
<li>It connected the cities of Philadelphia and Lancaster in the state of Pennsylvania.</li>
<li>It was sixty-two miles long.</li>
</ul>
<p>The student wants to emphasize the distance covered by the Philadelphia and Lancaster Turnpike. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #304 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Meteorites found on Earth are divided into two categories. • A meteorite that was observed falling to Earth before being recovered is known as a meteorite fall. • All other meteorites found on Earth are known as meteorite finds. • There have been about 1,200 recorded meteorite falls. • There have been over 60,000 recorded meteorite finds. The student wants to contrast the number of meteorite falls with the number of meteorite finds. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) A meteorite that was observed falling to Earth before being recovered is known as a meteorite fall; all others are known as meteorite finds.
(B) Meteorites found on Earth are divided into two categories: meteorite falls and meteorite finds.
(C) There have been about 1,200 recorded meteorite falls, or meteorites observed falling to Earth.
(D) While there have been only about 1,200 recorded meteorite falls, there have been over 60,000 meteorite finds.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.63
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Minnesota defines a lake as an inland body of water of at least 10 acres.
Wisconsin’s definition of a lake doesn’t take size into account.
By its own definition, Wisconsin has over 15,000 lakes, many smaller than 10 acres.
By Minnesota’s definition, Wisconsin has only about 6,000 lakes.
The student wants to contrast Minnesota’s definition of a lake with Wisconsin’s. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Wisconsin, which doesn’t take size into account in defining a lake, claims that it has over 15,000 lakes.
(B) Because its definition of a lake is different from Minnesota’s, it is unclear how many lakes Wisconsin really has.
(C) According to Minnesota’s definition of a lake—an inland body of water of at least 10 acres—Wisconsin has about 6,000 lakes.
(D) Minnesota’s definition of a lake—an inland body of water of at least 10 acres—is more restrictive than Wisconsin’s, which doesn’t take size into account.
Suggested correct answer: D
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Minnesota defines a lake as an inland body of water of at least 10 acres.</li>
<li>Wisconsin’s definition of a lake doesn’t take size into account.</li>
<li>By its own definition, Wisconsin has over 15,000 lakes, many smaller than 10 acres.</li>
<li>By Minnesota’s definition, Wisconsin has only about 6,000 lakes.</li>
</ul>
<p>The student wants to contrast Minnesota’s definition of a lake with Wisconsin’s. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #303 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • In World War I, US soldiers who were members of the Choctaw Nation in Oklahoma participated in the Choctaw Code Talkers program. • The Choctaw Code Talkers were trained to relay coded military information in their native language. • In World War II, the US Army recruited Navajo (Diné) soldiers to transmit coded messages in their native language. • These soldiers were known as the Navajo Code Talkers. The student wants to emphasize a similarity between the Choctaw Code Talkers and the Navajo Code Talkers. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) US soldiers who were members of the Choctaw Nation in Oklahoma used their native language to relay coded information.
(B) In World War II, one group of Navajo (Diné) soldiers was known as the Navajo Code Talkers.
(C) Both the Choctaw Code Talkers and the Navajo Code Talkers transmitted coded military messages in the soldiers’ native languages.
(D) The Choctaw Code Talkers, not the Navajo Code Talkers, served in World War I.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Seven species of sea turtle exist today.
Five sea turtle species can be found in the Atlantic Ocean.
One of those species is the Kemp’s ridley sea turtle.
Its scientific name is Lepidochelys kempii .
Another of those species is the olive ridley sea turtle.
Its scientific name is Lepidochelys olivacea .
The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Among the seven species of sea turtle is the olive ridley sea turtle, which can be found in the Atlantic Ocean.
(B) The Kemp’s ridley sea turtle is referred to as Lepidochelys kempii , while the olive ridley sea turtle is referred to as Lepidochelys olivacea .
(C) Both the Kemp’s ridley sea turtle and the olive ridley sea turtle can be found in the Atlantic Ocean.
(D) The Kemp’s ridley sea turtle (Lepidochelys kempii ) and the olive ridley sea turtle (Lepidochelys olivacea ) are different species.
Suggested correct answer: C
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Seven species of sea turtle exist today.</li>
<li>Five sea turtle species can be found in the Atlantic Ocean.</li>
<li>One of those species is the Kemp’s ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys kempii</em>.</li>
<li>Another of those species is the olive ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys olivacea</em>.</li>
</ul>
<p>The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #302 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Biographer Michael Gorra notes that the novelist Henry James “lived in a world of second thoughts,” frequently tinkering with his novels and stories after their initial publication. However, the differences between the 1881 first edition and the 1908 edition of his novel A Portrait of a Lady are extreme, even by James’s standards; _______ some critics regard the two editions as two different novels altogether. Which choice completes the text with the most logical transition?
(A) by contrast,
(B) in fact,
(C) nevertheless,
(D) in other words,
Corrected stem text Biographer Michael Gorra notes that the novelist Henry James “lived in a world of second thoughts,” frequently tinkering with his novels and stories after their initial publication. However, the differences between the 1881 first edition and the 1908 edition of his novel A Portrait of a Lady are extreme, even by James’s standards; _______ some critics regard the two editions as two different novels altogether. Which choice completes the text with the most logical transition? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #301 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The liquid metals in Earth’s core circulate constantly, and this circulation generates electrical currents that flow between Earth’s North and South magnetic poles. These electrical currents, _______ create a barrier around Earth that protects us from radiation and charged particles coming from space. Which choice completes the text with the most logical transition?
(A) in turn,
(B) likewise,
(C) nevertheless,
(D) in reality,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified) Earth’s auroras—colorful displays of light seen above the northern and southern poles—result, broadly speaking, from the Sun’s activity. ______ blank the Sun releases charged particles that are captured by Earth’s magnetic field and channeled toward the poles. These particles then collide with atoms in the atmosphere, causing the atoms to emit auroral light.
Which choice completes the text with the most logical transition?
Suggested correct answer: A
Verified stem text <p>Earth’s auroras—colorful displays of light seen above the northern and southern poles—result, broadly speaking, from the Sun’s activity. <span>______</span><span class="sr-only">blank</span> the Sun releases charged particles that are captured by Earth’s magnetic field and channeled toward the poles. These particles then collide with atoms in the atmosphere, causing the atoms to emit auroral light.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #300 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) After appropriate permissions are granted, a typical archaeological dig begins with a surveyor making a detailed grid of the excavation site. Then, the site is carefully dug, and any artifacts found are recorded and mapped onto the site grid. _______ the artifacts are removed, cataloged, and analyzed in a laboratory. Which choice completes the text with the most logical transition?
(A) For instance,
(B) On the contrary,
(C) Earlier,
(D) Finally,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) To explore how blinking affects social interactions, Dutch researchers observed interactions between human speakers and “listeners” (animated human faces on a screen). The researchers found that when the listeners blinked slowly, the speakers tended to talk for less time. ______ blank quicker blinks were associated with longer talking times.
Which choice completes the text with the most logical transition?
Suggested correct answer: D
Verified stem text <p>To explore how blinking affects social interactions, Dutch researchers observed interactions between human speakers and “listeners” (animated human faces on a screen). The researchers found that when the listeners blinked slowly, the speakers tended to talk for less time. <span>______</span><span class="sr-only">blank</span> quicker blinks were associated with longer talking times.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #299 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #298 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #297 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Latin America is known to have dozens, if not hundreds, of popular dance forms. Only five of these dances are included in international ballroom dance _______ rumba, samba, cha-cha-cha, paso doble, and jive—the last of which is grouped with the other Latin dances despite not having Latin roots. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) competitions, however:
(B) competitions, however,
(C) competitions, however;
(D) competitions; however,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.51
Bank-match candidate (unverified) Earth is not a perfect sphere. Due to the ______ blank gravitational pull, Earth bulges out on the sides closest to and farthest from the Moon. This distorting pull is known as a tidal force, and it is responsible for the changes in water levels that are called high and low tides.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: A
Verified stem text <p>Earth is not a perfect sphere. Due to the <span>______</span><span class="sr-only">blank</span> gravitational pull, Earth bulges out on the sides closest to and farthest from the Moon. This distorting pull is known as a tidal force, and it is responsible for the changes in water levels that are called high and low tides.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #293 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) One of the few African American global explorers during the turn of the 20th century, _______ Which choice completes the text so that it conforms to the conventions of Standard English?
(A) Matthew Henson made several treks across Greenland between 1891 and 1909.
(B) 1891 and 1909 were the years between which Matthew Henson made several treks across Greenland.
(C) Greenland was where Matthew Henson made several treks between 1891 and 1909.
(D) several treks across Greenland were made by Matthew Henson between 1891 and 1909.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Far from being modern inventions, ______ blank more than 5,000 years ago.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) Sumerians in ancient Mesopotamia used drinking straws
(B) drinking straws were used by Sumerians in ancient Mesopotamia
(C) the use of drinking straws by Sumerians in ancient Mesopotamia happened
(D) ancient Mesopotamia was home to Sumerians who used drinking straws
Suggested correct answer: B mismatches stored answer "A" -- double check
Verified stem text <p>Far from being modern inventions, <span>______</span><span class="sr-only">blank</span> more than 5,000 years ago.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #292 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #287 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) “Lines Written in Early Spring” is a 1798 poem by William Wordsworth. In the poem, the speaker describes having contradictory feelings while experiencing the sights and sounds of a spring day: _______ Which quotation from “Lines Written in Early Spring” most effectively illustrates the claim?
(A) “Through primrose-tufts, in that sweet bower, / The periwinkle trail’d its wreathes; / And ’tis my faith that every flower / Enjoys the air it breathes.”
(B) “The budding twigs spread out their fan, / To catch the breezy air; / And I must think, do all I can, / That there was pleasure there.”
(C) “The birds around me hopp’d and play’d: / Their thoughts I cannot measure, / But the least motion which they made, / It seem’d a thrill of pleasure.”
(D) “I heard a thousand blended notes, / While in a grove I [sat] reclined, / In that sweet mood when pleasant thoughts / Bring sad thoughts to the mind.”
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) “Ghosts of the Old Year” is an early 1900s poem by James Weldon Johnson. In the poem, the speaker describes experiencing an ongoing cycle of anticipation followed by regretful reflection: ______ blank
Which quotation from “Ghosts of the Old Year” most effectively illustrates the claim?
(A) “What does this brazen tongue declare, / That falling on the midnight air / Brings to my heart a sense of care / Akin to fright?”
(B) “The snow has ceased its fluttering flight, / The wind sunk to a whisper light, / An ominous stillness fills the night, / A pause—a hush.”
(C) “It tells of many a squandered day, / Of slighted gems and treasured clay, / Of precious stores not laid away, / Of fields unreaped.”
(D) “And so the years go swiftly by, / Each, coming, brings ambitions high, / And each, departing, leaves a sigh / Linked to the past.”
Suggested correct answer: D
Verified stem text <p>“Ghosts of the Old Year” is an early 1900s poem by James Weldon Johnson. In the poem, the speaker describes experiencing an ongoing cycle of anticipation followed by regretful reflection: <span>______</span><span class="sr-only">blank</span></p>
<p>Which quotation from “Ghosts of the Old Year” most effectively illustrates the claim?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #276 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #273 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The ancient Arab dhow was a sailing vessel distinguishable by its triangular sails and stitched hull construction. • Dhows were used primarily for trade along the coasts of Arab, South Asian, and East African countries. • Contemporary shipbuilders in Oman use a mix of modern and traditional materials to build replicas of ancient dhows. • Most of the materials used are traditional. • Replica hulls are stitched together using the same traditional coconut palm fiber rope used on the hulls of ancient dhows. The student wants to make a generalization about the materials used in dhow replicas. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) A traditional material that was used to stitch together the hulls of ancient dhows, coconut palm fiber rope is still used by shipbuilders.
(B) The ancient Arab dhow was a sailing vessel used primarily for trade and distinguishable by its triangular sails.
(C) Although most materials used in dhow replicas are traditional, some modern materials are used.
(D) Contemporary shipbuilders in Oman build replicas of the dhow, which was an ancient sailing vessel with a stitched hull construction.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.57; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Astronomers estimate that the number of comets orbiting the Sun is in the billions.
81P/Wild is one of many comets whose orbit has changed over time.
81P/Wild’s orbit once lay between the orbits of Uranus and Jupiter.
The comet’s orbit is now positioned between the orbits of Jupiter and Mars.
The student wants to make and support a generalization about the orbits of comets. Which choice most effectively uses relevant information from the notes to accomplish these goals?
(A) Astronomers estimate that the number of comets orbiting the Sun is in the billions; the comets’ orbits may change over time.
(B) Like Uranus, Jupiter, and Mars, billions of comets orbit the Sun.
(C) One example of a comet is 81P/Wild, whose orbit around the Sun once lay between Uranus’s and Jupiter’s orbits but is now positioned between those of Jupiter and Mars.
(D) A comet’s orbit around the Sun may change over time: the orbit of comet 81P/Wild once lay between the orbits of Uranus and Jupiter but is now positioned between those of Jupiter and Mars.
Suggested correct answer: D mismatches stored answer "B" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Astronomers estimate that the number of comets orbiting the Sun is in the billions.</li>
<li>81P/Wild is one of many comets whose orbit has changed over time.</li>
<li>81P/Wild’s orbit once lay between the orbits of Uranus and Jupiter.</li>
<li>The comet’s orbit is now positioned between the orbits of Jupiter and Mars.</li>
</ul>
<p>The student wants to make and support a generalization about the orbits of comets. Which choice most effectively uses relevant information from the notes to accomplish these goals? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #272 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Elizabeth Catlett’s sculpture Recognition (1970) shows two African American figures with rounded, indistinct features. • The figures reach out to each other in a pose that symbolizes a close, supportive relationship. • Her sculpture StudentsAspire (1978) shows two African American figures with sharply defined features. • The figures hold an equal sign above their heads with one hand and embrace each other with the other hand. • This pose symbolizes their support for each other in the pursuit of equality. The student wants to emphasize a similarity between the two sculptures. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Catlett’s StudentsAspire depicts two figures supporting each other in the pursuit of equality.
(B) Recognition and StudentsAspire both show African American figures in poses that symbolize supportive relationships.
(C) Catlett completed Recognition in 1970 and StudentsAspire in 1978.
(D) The figures in Recognition have features that are rounded and indistinct, while the figures in StudentsAspire have sharply defined features.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Seven species of sea turtle exist today.
Five sea turtle species can be found in the Atlantic Ocean.
One of those species is the Kemp’s ridley sea turtle.
Its scientific name is Lepidochelys kempii .
Another of those species is the olive ridley sea turtle.
Its scientific name is Lepidochelys olivacea .
The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Among the seven species of sea turtle is the olive ridley sea turtle, which can be found in the Atlantic Ocean.
(B) The Kemp’s ridley sea turtle is referred to as Lepidochelys kempii , while the olive ridley sea turtle is referred to as Lepidochelys olivacea .
(C) Both the Kemp’s ridley sea turtle and the olive ridley sea turtle can be found in the Atlantic Ocean.
(D) The Kemp’s ridley sea turtle (Lepidochelys kempii ) and the olive ridley sea turtle (Lepidochelys olivacea ) are different species.
Suggested correct answer: C
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Seven species of sea turtle exist today.</li>
<li>Five sea turtle species can be found in the Atlantic Ocean.</li>
<li>One of those species is the Kemp’s ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys kempii</em>.</li>
<li>Another of those species is the olive ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys olivacea</em>.</li>
</ul>
<p>The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #271 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • In the 1930s, the Imperial Sugar Cane Institute in India sought to limit the country’s dependence on imported sugarcane. • The institute enlisted botanist Janaki Ammal to breed a local variety of sugarcane. • She crossbred the imported sugarcane species Saccharum officinarum with grasses native to India. • She succeeded in creating sugarcane hybrids well suited to India’s climate. The student wants to emphasize Janaki Ammal’s achievement. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) By crossbreeding the imported sugarcane species Saccharum officinarum with grasses native to India, Ammal succeeded in creating sugarcane hybrids well suited to India’s climate.
(B) In the 1930s, the Imperial Sugar Cane Institute, which enlisted Ammal, sought to limit dependence on imported sugarcane.
(C) Ammal was enlisted by the Imperial Sugar Cane Institute at a time when a local variety of sugarcane needed to be produced.
(D) As part of efforts to breed a local variety of sugarcane, an imported sugarcane species called Saccharum officinarum was crossbred with grasses native to India.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.56; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Seven species of sea turtle exist today.
Five sea turtle species can be found in the Atlantic Ocean.
One of those species is the Kemp’s ridley sea turtle.
Its scientific name is Lepidochelys kempii .
Another of those species is the olive ridley sea turtle.
Its scientific name is Lepidochelys olivacea .
The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Among the seven species of sea turtle is the olive ridley sea turtle, which can be found in the Atlantic Ocean.
(B) The Kemp’s ridley sea turtle is referred to as Lepidochelys kempii , while the olive ridley sea turtle is referred to as Lepidochelys olivacea .
(C) Both the Kemp’s ridley sea turtle and the olive ridley sea turtle can be found in the Atlantic Ocean.
(D) The Kemp’s ridley sea turtle (Lepidochelys kempii ) and the olive ridley sea turtle (Lepidochelys olivacea ) are different species.
Suggested correct answer: C mismatches stored answer "A" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Seven species of sea turtle exist today.</li>
<li>Five sea turtle species can be found in the Atlantic Ocean.</li>
<li>One of those species is the Kemp’s ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys kempii</em>.</li>
<li>Another of those species is the olive ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys olivacea</em>.</li>
</ul>
<p>The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #269 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The Inca of South America used intricately knotted string devices called quipus to record countable information, like population data and payments. _______ they may have used quipus to record more complex information, like stories and myths, according to researchers. Which choice completes the text with the most logical transition?
(A) As a result,
(B) In other words,
(C) In addition,
(D) For example,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified) A 2017 study of sign language learners tested the role of iconicity—the similarity of a sign to the thing it represents—in language acquisition. The study found that the greater the iconicity of a sign, the more likely it was to have been learned. ______ blank the correlation between acquisition and iconicity was lower than that between acquisition and another factor studied: sign frequency.
Which choice completes the text with the most logical transition?
Suggested correct answer: C
Verified stem text <p>A 2017 study of sign language learners tested the role of iconicity—the similarity of a sign to the thing it represents—in language acquisition. The study found that the<strong> </strong>greater the iconicity of a sign, the more likely it was to have been learned. <span>______</span><span class="sr-only">blank</span> the correlation between acquisition and iconicity was lower than that between acquisition and another factor studied: sign frequency.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #267 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Before it unveiled a massive new gallery in 2009, the Art Institute of Chicago was only able to display about 5% of its art collection. _______ the museum is able to display close to 30% of its collection. Which choice completes the text with the most logical transition?
(A) Additionally,
(B) For example,
(C) Nevertheless,
(D) Today,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) The number of dark spots that appear on the Sun, known as sunspots, can vary greatly. For example, there were about 180 sunspots in November 2001. ______ blank there were only about 2 sunspots in December 2008.
Which choice completes the text with the most logical transition?
Suggested correct answer: D
Verified stem text <p>The number of dark spots that appear on the Sun, known as sunspots, can vary greatly. For example, there were about 180 sunspots in November 2001. <span>______</span><span class="sr-only">blank</span> there were only about 2 sunspots in December 2008.</p>
<p> </p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #262 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Researchers Amit Kumar and Nicholas Epley investigated how _______ In a series of experiments conducted in 2022, they found that people performing small acts of kindness underestimated the positive effect their actions had on others. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) do people perceive acts of kindness.
(B) do people perceive acts of kindness?
(C) people perceive acts of kindness?
(D) people perceive acts of kindness.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified) Compared to that of alumina glass, ______ blank silica glass atoms are so far apart that they are unable to re-form bonds after being separated.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) silica glass is at a significant disadvantage due to its more dispersed atomic arrangement:
(B) silica glass has a more dispersed atomic arrangement, resulting in a significant disadvantage:
(C) a significant disadvantage of silica glass is that its atomic arrangement is more dispersed:
(D) silica glass’s atomic arrangement is more dispersed, resulting in a significant disadvantage:
Suggested correct answer: D
Verified stem text <p>Compared to that of alumina glass, <span>______</span><span class="sr-only">blank</span> silica glass atoms are so far apart that they are unable to re-form bonds after being separated.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #259 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #257 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The Cretaceous pterosaur Tupandactylus navigans is known for having an anomalously oversized head crest. Until an almost complete fossil skeleton was found in Brazil, paleontologists had been able to study only skull specimens from T. navigans, though it was presumed that, like other pterosaurs, the species’s primary form of locomotion was powered flight. Examining the fuller skeleton in 2016, Victor Beccari and his team determined that T. navigans had long hind legs, short wings, and an unusually long neck—characteristics that, combined with the creature’s large-crested head, would have made sustained flight difficult and walking upright relatively comfortable. Based on these findings the team suggests that T. navigans likely _______ Which choice most logically completes the text?
(A) flew for longer distances than did other pterosaur species that had oversized head crests.
(B) had longer wings than other pterosaur species considered to have been comfortable walking.
(C) had a smaller head than researchers expected based on the earlier T. navigans skull specimens.
(D) flew for shorter distances and spent more time walking than researchers previously thought.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Scientists studying Mars long thought the history of its crust was relatively simple. One reason for this is that geologic and climate data collected by a spacecraft showed that the crust was largely composed of basalt, likely as a result of intense volcanic activity that brought about a magma ocean, which then cooled to form the planet’s surface. A study led by Valerie Payré focused on additional information—further analysis of data collected by the spacecraft and infrared wavelengths detected from Mars’s surface—that revealed the presence of surprisingly high concentrations of silica in certain regions on Mars. Since a planetary surface that formed in a mostly basaltic environment would be unlikely to contain large amounts of silica, Payré concluded that ______ blank
Which choice most logically completes the text?
(A) the information about silica concentrations collected by the spacecraft is likely more reliable than the silica information gleaned from infrared wavelengths detected from Mars’s surface.
(B) high silica concentrations on Mars likely formed from a different process than that which formed the crusts of other planets.
(C) having a clearer understanding of the composition of Mars’s crust and the processes by which it formed will provide more insight into how Earth’s crust formed.
(D) Mars’s crust likely formed as a result of other major geological events in addition to the cooling of a magma ocean.
Suggested correct answer: D
Verified stem text <p>Scientists studying Mars long thought the history of its crust was relatively simple. One reason for this is that geologic and climate data collected by a spacecraft showed that the crust was largely composed of basalt, likely as a result of intense volcanic activity that brought about a magma ocean, which then cooled to form the planet’s surface. A study led by Valerie Payré focused on additional information—further analysis of data collected by the spacecraft and infrared wavelengths detected from Mars’s surface—that revealed the presence of surprisingly high concentrations of silica in certain regions on Mars. Since a planetary surface that formed in a mostly basaltic environment would be unlikely to contain large amounts of silica, Payré concluded that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #255 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) It may seem that the optimal strategy for an animal pursuing prey or escaping predators is to move at maximal speed, but the energy expense of exploiting full speed capacity can disfavor such a strategy even in escape contexts, as evidenced by the fact that _______ Which choice most effectively uses data from the graph to complete the text?
(A) most lizard species use about the same percentage of their maximal speed when escaping predation as they do when pursuing prey.
(B) multiple lizard species move at an average of less than 90% of their maximal speed while escaping predation.
(C) more lizard species use, on average, 90%–100% of their maximal speed while escaping predation than use any other percentage of their maximal speed.
(D) at least 4 lizard species use, on average, less than 100% of their maximal speed while pursuing prey.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.43
Bank-match candidate (unverified) A heliograph is a semaphore device used for sending optical communications—usually in the form of Morse code—by reflecting flashes of sunlight off a mirror. Heliographs were used for rapid communication across expansive distances for military, surveying, and forestry purposes during the late nineteenth and early twentieth centuries, but they were largely effective only during the daytime, and the range of the device depended on factors such as the opacity of the air and line of sight. Therefore, heliographs were eventually replaced by technology that ______ blank
Which choice most logically completes the text?
(A) worked on similar principles but was easier to produce and maintain.
(B) was not so constrained by environmental circumstances.
(C) could be used for more than military, surveying, or forestry purposes.
(D) enabled communication that didn’t require knowledge of Morse code.
Suggested correct answer: B
Verified stem text <p>A heliograph is a semaphore device used for sending optical communications—usually in the form of Morse code—by reflecting flashes of sunlight off a mirror. Heliographs were used for rapid communication across expansive distances for military, surveying, and forestry purposes during the late nineteenth and early twentieth centuries, but they were largely effective only during the daytime, and the range of the device depended on factors such as the opacity of the air and line of sight. Therefore, heliographs were eventually replaced by technology that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #253 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The 2021 exhibition This Is the Day at Arkansas’s Crystal Bridges Museum of American Art featured works dealing with expressions of faith and spirituality in the Black community. The museum’s 2022 exhibition The Dirty South, meanwhile, focused on Black culture in the American South from 1920 to 2020, with a particular focus on the intersections between visual arts and music. Together, these exhibitions don’t merely highlight the diversity of the Black experience in the US; they also showcase the diverse media through which artists have depicted and engaged with that experience. Which statement about the exhibitions, if true, would most directly support the underlined claim?
(A) Between them, This Is the Day and The Dirty South included drawings, paintings, photographs, sculptures, textiles, videos, costumes, and music.
(B) This Is the Day included works by fewer than two dozen artists, whereas The Dirty South included works by more than 80 artists.
(C) This Is the Day exclusively included works in the permanent collection of the museum, whereas The Dirty South included works from multiple sources outside the museum.
(D) Between them, This Is the Day and The Dirty South included works depicting more than 300 years of Black experience in the United States.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Sandra Cisneros’s 1984 novella The House on Mango Street made a lasting impact on US literature. Its depiction of Mexican American culture inspired later authors to examine their own heritage within their fictional works. Also influential was the book’s portrayal of the main character, Esperanza, during a pivotal year of her youth. This insightful depiction of a preteen girl encouraged authors who, like Cisneros herself, are Latina to use fictional works to examine experiences from their own youth.
Which statement, if true, would most strongly support the claim in the underlined sentence?
(A) In interviews, a number of Latina authors say that The House on Mango Street inspired them to write about their own adolescence in their novels.
(B) In published writings, several prominent authors who are not Latina say that reading The House on Mango Street influenced their approach to writing fiction.
(C) The House on Mango Street has sold over six million copies and is one of the most commonly read books among high school and university students in the US.
(D) Since 1984, new novels about young Latina characters by Latina authors have often been compared to The House on Mango Street .
Suggested correct answer: A
Verified stem text <p>Sandra Cisneros’s 1984 novella <em>The House on Mango Street</em> made a lasting impact on US literature. Its depiction of Mexican American culture inspired later authors to examine their own heritage within their fictional works. Also influential was the book’s portrayal of the main character, Esperanza, during a pivotal year of her youth. <span role="region" aria-label="Referenced Content"><u>This insightful depiction of a preteen girl encouraged authors who, like Cisneros herself, are Latina to use fictional works to examine experiences from their own youth.</u></span></p>
<p>Which statement, if true, would most strongly support the claim in the underlined sentence?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #250 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #249 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Text 1 In 1954 George Balanchine choreographed a production of The Nutcracker, a ballet by Pyotr Ilyich Tchaikovsky. It has since become a tradition for hundreds of dance companies in North America to stage The Nutcracker each year. But the show is stuck in the past, with an old-fashioned story and references, so it should no longer be produced. Ballet needs to create new traditions if it wants to stay relevant to contemporary audiences. Text 2 The Nutcracker is outdated, but it should be kept because it’s a holiday favorite and provides substantial income for some dance companies. Although it can be behind the times, there are creative ways to update the show. For example, Debbie Allen successfully modernized the story. Her show Hot Chocolate Nutcracker combines ballet, tap, hip-hop, and other styles, and it has been gaining in popularity since it opened in 2009. Based on the texts, how would the author of Text 2 most likely respond to the underlined claim in Text 1?
(A) By questioning the idea that the story of The Nutcracker is stuck in the past and by rejecting the suggestion that contemporary audiences would enjoy an updated version
(B) By agreeing that contemporary audiences have largely stopped going to see performances of The Nutcracker because it’s so old-fashioned
(C) By pointing out that most dance companies could increase their incomes by offering modernized versions of The Nutcracker
(D) By suggesting that dance companies should consider offering revised versions of The Nutcracker instead of completely rejecting the show
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.47
Bank-match candidate (unverified)
Text 1
In 2007, a team led by Alice Storey analyzed a chicken bone found in El Arenal, Chile, dating it to 1321–1407 CE—over a century before Europeans invaded the region, bringing their own chickens. Storey also found that the El Arenal chicken shared a unique genetic mutation with the ancient chicken breeds of the Polynesian Islands in the Pacific. Thus, Polynesian peoples, not later Europeans, probably first introduced chickens to South America.
Text 2
An Australian research team weakened the case for a Polynesian origin for the El Arenal chicken by confirming that the mutation identified by Storey has occurred in breeds from around the world. More recently, though, a team led by Agusto Luzuriaga-Neira found that South American chicken breeds and Polynesian breeds share other genetic markers that European breeds lack. Thus, the preponderance of evidence now favors a Polynesian origin.
Based on the texts, how would the author of Text 2 most likely respond to the underlined claim in Text 1?
(A) By broadly agreeing with the claim but objecting that the timeline it presupposes conflicts with the findings of the genetic analysis conducted by Storey’s team
(B) By faulting the claim for implying that domestic animals couldn’t have been transferred from South America to the Polynesian Islands as well
(C) By critiquing the claim for being based on an assumption that before the European invasion of South America, the chickens of Europe were genetically uniform
(D) By noting that while the claim is persuasive, the findings of Luzuriaga-Neira’s team provide stronger evidence for it than the findings of the genetic analysis conducted by Storey do
Suggested correct answer: D
Verified stem text <p> </p><p><span role="heading"><strong>Text 1</strong></span></p>
<p>In 2007, a team led by Alice Storey analyzed a chicken bone found in El Arenal, Chile, dating it to 1321–1407 CE—over a century before Europeans invaded the region, bringing their own chickens. Storey also found that the El Arenal chicken shared a unique genetic mutation with the ancient chicken breeds of the Polynesian Islands in the Pacific. Thus, <span role="region" aria-label="Referenced Content"><u>Polynesian peoples, not later Europeans, probably first introduced chickens to South America. </u></span></p>
<p> </p><p><span role="heading"><strong>Text 2</strong></span></p>
<p>An Australian research team weakened the case for a Polynesian origin for the El Arenal chicken by confirming that the mutation identified by Storey has occurred in breeds from around the world. More recently, though, a team led by Agusto Luzuriaga-Neira found that South American chicken breeds and Polynesian breeds share other genetic markers that European breeds lack. Thus, the preponderance of evidence now favors a Polynesian origin.</p>
<p>Based on the texts, how would the author of Text 2 most likely respond to the underlined claim in Text 1?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #247 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) When classical pianist Martha Argerich performs, it appears as if the music is coming to her spontaneously. She’s highly skilled technically, but because of how freely she plays and her willingness to take risks, she seems relaxed and natural. Her apparent ease, however, is due to a tremendous amount of preparation. Despite Argerich’s experience and virtuosity, she never takes for granted that she knows a piece of music. Instead, she approaches the music as if encountering it for the first time and tries to understand it anew. Which choice best states the main purpose of the text?
(A) To provide details about how Argerich identifies which pieces of music she will perform
(B) To assert that Argerich’s performances look effortless because of how she prepares for them
(C) To discuss the kinds of music Argerich feels most comfortable encountering for the first time
(D) To describe the unique way that Argerich approaches music she hasn’t performed before
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.43
Bank-match candidate (unverified) Text 1
Stage lighting theorist Adolphe Appia was perhaps the first to argue that light must be considered alongside all the various elements of a stage to create a single, unified performance. Researcher Kelly Bremner, however, has noted that Appia lacked technical expertise in the use of light in the theater. As a result of Appia’s inexperience, Bremner argues, Appia’s theory of light called for lighting practices that weren’t possible until after the advent of electricity around 1881.
Text 2
Adolphe Appia was not an amateur in the practice of lighting. Instead, it is precisely his exposure to lighting techniques at the time that contributed to his theory on the importance of light. When working as an apprentice for a lighting specialist in his youth, Appia observed the use of portable lighting devices that could be operated by hand. This experience developed his understanding of what was possible in the coordination of elements on the stage.
Based on the texts, how would the author of Text 2 most likely respond to the claim about Appia’s level of technical expertise made by Bremner in Text 1?
(A) Many lighting technicians dismissed Appia’s ideas about light on the stage.
(B) Appia likely gained a level of technical expertise during his time as an apprentice.
(C) Theater practitioners who worked with Appia greatly admired his work.
(D) Appia was unfamiliar with the use of music and sound in theater.
Suggested correct answer: B
Verified stem text <p><strong>Text 1</strong></p>
<p>Stage lighting theorist Adolphe Appia was perhaps the first to argue that light must be considered alongside all the various elements of a stage to create a single, unified performance. Researcher Kelly Bremner, however, has noted that Appia lacked technical expertise in the use of light in the theater. As a result of Appia’s inexperience, Bremner argues, Appia’s theory of light called for lighting practices that weren’t possible until after the advent of electricity around 1881. </p>
<p> </p>
<p><strong>Text 2</strong></p>
<p>Adolphe Appia was not an amateur in the practice of lighting. Instead, it is precisely his exposure to lighting techniques at the time that contributed to his theory on the importance of light. When working as an apprentice for a lighting specialist in his youth, Appia observed the use of portable lighting devices that could be operated by hand. This experience developed his understanding of what was possible in the coordination of elements on the stage.</p>
<p>Based on the texts, how would the author of Text 2 most likely respond to the claim about Appia’s level of technical expertise made by Bremner in Text 1?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #245 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While recent scholarship has undermined claims that the works of twelfth-century Islamic philosopher Ibn Rushdwere _______ other Muslim philosophers of his time, it is indisputable that his location in the Muslim-ruled area of what is now Spain meant that his works were primarily available thousands of miles west of the era’s center of Islamic thought. Which choice completes the text with the most logical and precise word or phrase?
(A) controversial among
(B) antagonistic toward
(C) imitated by
(D) inconsequential to
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.46
Bank-match candidate (unverified) Arturo A. Schomburg was dedicated to preserving books, art, and other materials from peoples of African descent around the world. To get these items, Schomburg ______ blank friends and colleagues, whom he asked to bring back rare and valuable objects from their international travels. Now, Schomburg’s collection is a valuable resource for scholars of Black history and culture.
Which choice completes the text with the most logical and precise word or phrase?
Suggested correct answer: D
Verified stem text <p>Arturo A. Schomburg was dedicated to preserving books, art, and other materials from peoples of African descent around the world. To get these items, Schomburg <span>______</span><span class="sr-only">blank</span> friends and colleagues, whom he asked to bring back rare and valuable objects from their international travels. Now, Schomburg’s collection is a valuable resource for scholars of Black history and culture.</p>
<p>Which choice completes the text with the most logical and precise word or phrase?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #244 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The following text is adapted from James Baldwin’s 1956 novel Giovanni’s Room. The narrator is riding in a taxi down a street lined with food vendors and shoppers in Paris, France. The multitude of Paris seems to be dressed in blue every day but Sunday, when, for the most part, they put on an unbelievably festive black. Here they were now, in blue, disputing , every inch, our passage, with their wagons, handtrucks, their bursting baskets carried at an angle steeply self-confident on the back. ©1956 by James Baldwin As used in the text, what does the word “disputing” most nearly mean?
(A) Arguing about
(B) Disapproving of
(C) Asserting possession of
(D) Providing resistance to
Corrected stem text The following text is adapted from James Baldwin’s 1956 novel Giovanni’s Room. The narrator is riding in a taxi down a street lined with food vendors and shoppers in Paris, France. The multitude of Paris seems to be dressed in blue every day but Sunday, when, for the most part, they put on an unbelievably festive black. Here they were now, in blue, §U§disputing§, every inch, our passage, with their wagons, handtrucks, their bursting baskets carried at an angle steeply self-confident on the back. ©1956 by James Baldwin As used in the text, what does the word “disputing” most nearly mean? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #242 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) 2 In editor Lisa Yaszek’s introduction to her anthology The Future Is Female! More Classic Science Fiction Stories by Women, Yaszek identifies an increasing senseof _______ feminist mode of writing in the 1970s, in contrast to many woman-authored science fiction stories of the 1920s to 1960s whose politics were less deliberately signaled. Which choice completes the text with the most logical and precise word or phrase?
(A) a prudently
(B) an overtly
(C) a cordially
(D) an inadvertently
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified) Although science fiction was dominated mostly by white male authors when Octavia Butler, a Black woman, began writing, she did not view the genre as ______ blank : Butler broke into the field with the publication of several short stories and her 1976 novel Patternmaster , and she later became the first science fiction writer to win a prestigious MacArthur Fellowship.
Which choice completes the text with the most logical and precise word or phrase?
Suggested correct answer: B
Verified stem text <p>Although science fiction was dominated mostly by white male authors when Octavia Butler, a Black woman, began writing, she did not view the genre as <span>______</span><span class="sr-only">blank</span>: Butler broke into the field with the publication of several short stories and her 1976 novel <em>Patternmaster</em>, and she later became the first science fiction writer to win a prestigious MacArthur Fellowship.</p>
<p>Which choice completes the text with the most logical and precise word or phrase?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #241 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #239 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) A circle in the xy-plane has its center at ( −1, 1). Line t is tangent to this circle at the point ( 5, −4). Which of the following points also lies on line t ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.66; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) A circle in the xy -plane has its center at ( − 4 , − 6 ) \left(- 4 , - 6\right) ( − 4 , − 6 ) . Line k k k is tangent to this circle at the point ( − 7 , − 7 ) \left(- 7 , - 7\right) ( − 7 , − 7 ) . What is the slope of line k k k ?
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p style="text-align: left;">A circle in the <em>xy</em>-plane has its center at <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mo>−</mo><mn>4</mn><mo separator="true">,</mo><mo>−</mo><mn>6</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(- 4 , - 6\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">−</span><span class="mord">4</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">6</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. Line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span> is tangent to this circle at the point <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mo>−</mo><mn>7</mn><mo separator="true">,</mo><mo>−</mo><mn>7</mn><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(- 7 , - 7\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">−</span><span class="mord">7</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">−</span><span class="mord">7</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span>. What is the slope of line <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal" style="margin-right:0.0315em;">k</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #238 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The function P models the population, in thousands, of a certain city t years after 2003. According to the model, the population is predicted to increase by 4% every n months. What is the value of n ?
(A) 8
(B) 12
(C) 18
(D) 72
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.82; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) P ( t ) = 290 ( 1.04 ) ( 4 6 ) t P \left(t\right) = 290 \left(1.04\right)^{\left(\dfrac{4}{6}\right) t} P ( t ) = 290 ( 1.04 ) ( 6 4 ) t
The function P P P models the population, in thousands, of a certain city t t t years after 2005 2005 2005 . According to the model, the population is predicted to increase by n % n \% n % every 18 18 18 months. What is the value of n n n ?
Suggested correct answer: C mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi><mrow><mo fence="true">(</mo><mi>t</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>290</mn><msup><mrow><mo fence="true">(</mo><mn>1.04</mn><mo fence="true">)</mo></mrow><mrow><mrow><mo fence="true">(</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>4</mn><mn>6</mn></mfrac></mstyle><mo fence="true">)</mo></mrow><mi>t</mi></mrow></msup></mrow><annotation encoding="application/x-tex">P \left(t\right) = 290 \left(1.04\right)^{\left(\dfrac{4}{6}\right) t}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">t</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:2.7578em;vertical-align:-0.25em;"></span><span class="mord">290</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">1.04</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:2.5078em;"><span style="top:-4.5078em;margin-right:0.05em;"><span class="pstrut" style="height:3.3975em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="minner mtight"><span class="mopen sizing reset-size3 size6 mtight delimcenter" style="top:0.075em;"><span class="delimsizing size3 mtight"><span class="mtight">(</span></span></span><span class="mord sizing reset-size3 size6"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">6</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">4</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mclose sizing reset-size3 size6 mtight delimcenter" style="top:0.075em;"><span class="delimsizing size3 mtight"><span class="mtight">)</span></span></span></span><span class="mord mathnormal mtight">t</span></span></span></span></span></span></span></span></span></span></span></span></p>
<p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi></mrow><annotation encoding="application/x-tex">P</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span></span></span></span> models the population, in thousands, of a certain city <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> years after <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2005</mn></mrow><annotation encoding="application/x-tex">2005</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2005</span></span></span></span>. According to the model, the population is predicted to increase by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi><mi mathvariant="normal">%</mi></mrow><annotation encoding="application/x-tex">n \%</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord mathnormal">n</span><span class="mord">%</span></span></span></span> every <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>18</mn></mrow><annotation encoding="application/x-tex">18</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">18</span></span></span></span> months. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #236 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #232 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #230 · Full test · math · type: mcq
Source PDF page (reference) Question #229 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) In △ RST , the measure of ∠ R is 63° . Which of the following could be the measure, in degrees, of ∠ S ?
(A) 116
(B) 118
(C) 126
(D) 180
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.45
Bank-match candidate (unverified)
Which of the following could be an equation for a line of best fit for the data in the scatterplot?
Suggested correct answer: A
Verified stem text <div class="stimulus_reference ">
<div class="standalone_image ">
<img 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" alt="The figure presents a scatterplot in the x y plane. The numbers 0 through 5, in increments of 1, are indicated along the x-axis. The numbers 0 through 6, in increments of 1, are indicated along the y-axis. There are 11 data points in the scatterplot. The data points begin on the y-axis at 6, and trend almost linearly downward and to the right. The data points end at the point with coordinates 5 comma 1." /></div>
</div>
<p class="stem_paragraph ">Which of the following could be an equation for a line of best fit for the data in the scatterplot?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #226 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #224 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The scatterplot shows the relationship between two variables x and y. A line of best fit for the data is also shown. For how many of the 10 data points is the actual y-value greater than the y-value predicted by the line of best fit?
(A) 3
(B) 4
(C) 6
(D) 7
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.73; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The scatterplot shows the relationship between two variables, x x x and y y y . A line of best fit for the data is also shown. Which of the following is closest to the difference between the y y y -coordinate of the data point with x = 1 x = 1 x = 1 and the y y y -value predicted by the line of best fit at x = 1 x = 1 x = 1 ?
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <p class="stem_paragraph ">The scatterplot shows the relationship between two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>. A line of best fit for the data is also shown. Which of the following is closest to the difference between the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-coordinate of the data point with <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> and the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-value predicted by the line of best fit at <span class="math_expression "><span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span> ?</p><div class="standalone_image ">
<img 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" alt="The figure presents a scatterplot in the x y plane. The numbers 0 through 6, in increments of 1, are indicated on the x-axis. The numbers 6 through 12, in increments of 1, are indicated on the y-axis. There are 10 data points in the scatterplot. The data points begin at the point with coordinates 0 comma 12, and trend downward and to the right. The coordinates of the data points are as follows. Note that all values are approximate.
Point 1. 0, comma 12.
Point 2. 0 point 8, comma 11.
Point 3. 1, comma 12.
Point 4. 1 point 5, comma 10 point 3.
Point 5. 2, comma 10.
Point 6. 2 point 2, comma 9 point 2.
Point 7. 3, comma 9.
Point 8. 3 point 5, comma 8.
Point 9. 3 point 8, comma 8 point 3.
Point 10. 4, comma 7.
A line of best fit is also drawn. The line slants downward and to the right, passing through the point with approximate coordinates 1 comma 11, and the point with approximate coordinates 4 comma 7 point 5.
" /></div><p></p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #223 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The kinetic energy, in joules, of an object with mass 9 kilograms traveling at a speed of v meters per second is given by the function K, where . Which of the following is the best interpretation of K (34) = 5,202 in this context?
(A) The object traveling at 34 meters per second has a kinetic energy of 5,202 joules.
(B) The object traveling at 340 meters per second has a kinetic energy of 5,202 joules.
(C) The object traveling at 5,202 meters per second has a kinetic energy of 34 joules.
(D) The object traveling at 23,409 meters per second has a kinetic energy of 34 joules.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.54
Bank-match candidate (unverified) An object’s kinetic energy, in joules, is equal to the product of one-half the object’s mass, in kilograms, and the square of the object’s speed, in meters per second. What is the speed, in meters per second, of an object with a mass of 4 kilograms and kinetic energy of 18 joules?
Suggested correct answer: A
Verified stem text <p class="stem_paragraph ">An object’s kinetic energy, in joules, is equal to the product of one-half the object’s mass, in kilograms, and the square of the object’s speed, in meters per second. What is the speed, in meters per second, of an object with a mass of 4 kilograms and kinetic energy of 18 joules?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #221 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #219 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #217 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #216 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #215 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) Argon is placed inside a container with a constant volume. The graph shows the estimated pressure y, in pounds per square inch (psi), of the argon when its temperature is x kelvins. What is the estimated pressure of the argon, in psi, when the temperature is 600 kelvins?
(A) 6
(B) 12
(C) 300
(D) 600
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.55; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Oxygen gas is placed inside a tank with a constant volume. The graph shows the estimated temperature y y y , in kelvins, of the oxygen gas when its pressure is x x x atmospheres.
The line slants sharply up from left to right.
The line begins at the approximate point (1.6 comma 190).
The line passes through the following approximate points:
(3 comma 350)
(6 comma 700)
(8 comma 933)
What is the estimated temperature, in kelvins, of the oxygen gas when its pressure is 6 6 6 atmospheres?
Suggested correct answer: C mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: left;">Oxygen gas is placed inside a tank with a constant volume. The graph shows the estimated temperature <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>, in kelvins, of the oxygen gas when its pressure is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> atmospheres.</p>
<p style="text-align: center;"></p><svg height="285.92875pt" version="1.1" viewBox="0 0 304.82875 285.92875" width="304.82875pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" role="img" aria-label="Graph of a line in the x y plane with the origin labeled O. The x axis is labeled Pressure, in atmospheres. It ranges from 0 to 10 in increments of 1. The y axis is labeled Temperature, in kelvins. It ranges from 0 to 1,000 in increments of 100. Refer to long description.">
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<div role="region" aria-label="Long description for graph of a line" class="sr-only"><ul>
<li>The line slants sharply up from left to right.</li>
<li>The line begins at the approximate point (1.6 comma 190).</li>
<li>The line passes through the following approximate points:
<ul>
<li>(3 comma 350)</li>
<li>(6 comma 700)</li>
<li>(8 comma 933)</li>
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<p style="text-align: left;">What is the estimated temperature, in kelvins, of the oxygen gas when its pressure is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn></mrow><annotation encoding="application/x-tex">6</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">6</span></span></span></span> atmospheres?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #214 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #212 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The function f is defined by f (x) = ax2 {}^{2} 2 + bx + c, where a, b, and c are constants. The graph of in the xy-plane passes through the points (−3, 0) . If a is an integer greater than 1, which of the following could be the value of a + b ?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The function h h h is defined by h ( x ) = a x + b h \left(x\right) = a^{x} + b h ( x ) = a x + b , where a a a and b b b are positive constants. The graph of y = h ( x ) y = h \left(x\right) y = h ( x ) in the x y x y x y -plane passes through the points (0 0 0 , 10 10 10 ) and (− 2 -2 − 2 , 325 36 \dfrac{325}{36} 36 325 ). What is the value of a b a b ab ?
Suggested correct answer: C mismatches stored answer "A" -- double check
Verified stem text <p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi></mrow><annotation encoding="application/x-tex">h</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">h</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>h</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><msup><mi>a</mi><mi>x</mi></msup><mo>+</mo><mi>b</mi></mrow><annotation encoding="application/x-tex">h \left(x\right) = a^{x} + b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7477em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">a</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6644em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">x</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> are positive constants. The graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>h</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = h \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">x y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane passes through the points (<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>0</mn></mrow><annotation encoding="application/x-tex">0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>10</mn></mrow><annotation encoding="application/x-tex">10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">10</span></span></span></span>) and (<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>−</mo><mn>2</mn></mrow><annotation encoding="application/x-tex">-2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord">2</span></span></span></span>, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>325</mn><mn>36</mn></mfrac></mstyle></mrow><annotation encoding="application/x-tex">\dfrac{325}{36}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:2.0074em;vertical-align:-0.686em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.3214em;"><span style="top:-2.314em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">36</span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.677em;"><span class="pstrut" style="height:3em;"></span><span class="mord"><span class="mord">325</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.686em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span>). What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><mi>b</mi></mrow><annotation encoding="application/x-tex">a b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">ab</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #211 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #208 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #203 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #202 · Full test · math · type: mcqno answer key
Source PDF page (reference) Question #201 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #198 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) For a snowstorm in a certain town, the minimum rate of snowfall recorded was 0.6 inches per hour, and the maximum rate of snowfall recorded was 1.8 inches per hour. Which inequality is true for all values of , where represents a rate of snowfall, in inches per hour, recorded for this snowstorm?
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.41
Bank-match candidate (unverified) The total cost, in dollars, to rent a surfboard consists of a $ 25 \$ 25 $25 service fee and a $ 10 \$ 10 $10 per hour rental fee. A person rents a surfboard for t t t hours and intends to spend a maximum of $ 75 \$ 75 $75 to rent the surfboard. Which inequality represents this situation?
(B) 10 + 25 t ≤ 75 10 + 25 t \leq 75 10 + 25 t ≤ 75
(D) 25 + 10 t ≤ 75 25 + 10 t \leq 75 25 + 10 t ≤ 75
Suggested correct answer: D
Verified stem text <p style="text-align: left;">The total cost, in dollars, to rent a surfboard consists of a <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>25</mn></mrow><annotation encoding="application/x-tex">\$ 25</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$25</span></span></span></span> service fee and a <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>10</mn></mrow><annotation encoding="application/x-tex">\$ 10</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$10</span></span></span></span> per hour rental fee. A person rents a surfboard for <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>t</mi></mrow><annotation encoding="application/x-tex">t</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6151em;"></span><span class="mord mathnormal">t</span></span></span></span> hours and intends to spend a maximum of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="normal">$</mi><mn>75</mn></mrow><annotation encoding="application/x-tex">\$ 75</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8056em;vertical-align:-0.0556em;"></span><span class="mord">$75</span></span></span></span> to rent the surfboard. Which inequality represents this situation?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #197 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #190 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) What is the solution ( r, s) to the given system of equations?
(A) ( 6, 3)
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.74; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) x + y = 18 x + y = 18 x + y = 18
5 y = x 5 y = x 5 y = x
What is the solution ( x , y ) \left(x , y\right) ( x , y ) to the given system of equations?
(A) ( 15 , 3 ) \left(15 , 3\right) ( 15 , 3 )
(B) ( 16 , 2 ) \left(16 , 2\right) ( 16 , 2 )
(C) ( 17 , 1 ) \left(17 , 1\right) ( 17 , 1 )
(D) ( 18 , 0 ) \left(18 , 0\right) ( 18 , 0 )
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>+</mo><mi>y</mi><mo>=</mo><mn>18</mn></mrow><annotation encoding="application/x-tex">x + y = 18</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">18</span></span></span></span></p>
<p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>5</mn><mi>y</mi><mo>=</mo><mi>x</mi></mrow><annotation encoding="application/x-tex">5 y = x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">5</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span></p>
<p style="text-align: left;">What is the solution <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(x , y\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> to the given system of equations?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #189 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) - -- The graph of the linear function f is shown, where y = f (x). What is the y-intercept of the graph of f ?
(A) 16
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59
Bank-match candidate (unverified) The function f f f is defined by f ( x ) = 7 x − 84 f \left(x\right) = 7 x - 84 f ( x ) = 7 x − 84 . What is the x -intercept of the graph of y = f ( x ) y = f \left(x\right) y = f ( x ) in the xy -plane?
(A) ( − 12 , 0 ) \left(- 12 , 0\right) ( − 12 , 0 )
(B) ( − 7 , 0 ) \left(- 7 , 0\right) ( − 7 , 0 )
(C) ( 7 , 0 ) \left(7 , 0\right) ( 7 , 0 )
(D) ( 12 , 0 ) \left(12 , 0\right) ( 12 , 0 )
Suggested correct answer: D
Verified stem text <p style="text-align: left;">The function <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi></mrow><annotation encoding="application/x-tex">f</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8889em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span></span></span></span> is defined by <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow><mo>=</mo><mn>7</mn><mi>x</mi><mo>−</mo><mn>84</mn></mrow><annotation encoding="application/x-tex">f \left(x\right) = 7 x - 84</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">7</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">84</span></span></span></span>. What is the <em>x</em>-intercept of the graph of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mi>f</mi><mrow><mo fence="true">(</mo><mi>x</mi><mo fence="true">)</mo></mrow></mrow><annotation encoding="application/x-tex">y = f \left(x\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathnormal" style="margin-right:0.1076em;">f</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> in the <em>xy</em>-plane?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #188 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) The graph of a system of a linear equation and a nonlinear equation is shown. What is the solution ( x, y) to this system?
(A) (0, 0)
(C) (4, 5)
(D) (5, 0) 2 On the first day of a semester, a film club has 90 members. Each day after the first day of the semester, 10 new members join the film club. If no members leave the film club, how many total members will the film club have 4 days after the first day of the semester? A) 400 B) 130 C) 94 D) 90 1
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.55
Bank-match candidate (unverified)
y = 2 x + 3 and x = 1 y = 2 x + 3\ \text{and}\ x = 1 y = 2 x + 3 and x = 1
What is the solution ( x , y ) \left(x, y\right) ( x , y ) to the given system of equations?
Suggested correct answer: B
Verified stem text <div class="stimulus_reference ">
<p class="standalone_statement style:1 ">
<span class="math_expression ">
<span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi><mo>=</mo><mn>2</mn><mi>x</mi><mo>+</mo><mn>3</mn><mtext> and </mtext><mi>x</mi><mo>=</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">y = 2 x + 3\ \text{and}\ x = 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">2</span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord">3</span><span class="mspace"> </span><span class="mord text"><span class="mord">and</span></span><span class="mspace"> </span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span></span></span>
</p>
</div>
<p class="stem_paragraph ">What is the solution <span class="math-container"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(x, y\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span></span> to the given system of equations?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #187 · Full test · math · type: grid_in
Source PDF page (reference) Question #186 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Earthquakes start at a point called a “focus” and spread out from there as seismic waves. • The two types of seismic waves that travel beneath Earth’s surface are primary waves (P waves) and secondary waves (S waves). • P waves travel more quickly beneath Earth’s surface than do S waves. • P waves compress and expand the ground, causing it to move backward and forward. • S waves cause the ground to move from side to side. The student wants to emphasize a similarity between P waves and S waves. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) P waves and S waves both travel beneath Earth’s surface, causing the ground to move.
(B) P waves travel away from an earthquake’s starting point at a higher rate of speed than do S waves.
(C) Spreading out from the focus of an earthquake, P waves move the ground backward and forward.
(D) Although P waves and S waves start at the same point, they behave very differently.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.61; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Mexican tetras are a fish species with two distinct populations.
Surface-dwelling tetras live on the surface and are able to see.
Cave-dwelling tetras live in total darkness and have lost the ability to see.
Cave-dwelling tetras have asymmetrical skulls with more sensory receptors on one side than the other.
These receptors help cave-dwelling tetras navigate in darkness.
The student wants to emphasize a difference between surface-dwelling and cave-dwelling tetras. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Surface-dwelling and cave-dwelling tetras may belong to the same species, but they are quite different.
(B) Cave-dwelling tetras can no longer see but use sensory receptors on their skulls to navigate.
(C) Mexican tetras are a fish species with two distinct populations: surface-dwelling tetras and cave-dwelling tetras.
(D) Surface-dwelling tetras can see, whereas cave-dwelling tetras cannot.
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Mexican tetras are a fish species with two distinct populations.</li>
<li>Surface-dwelling tetras live on the surface and are able to see.</li>
<li>Cave-dwelling tetras live in total darkness and have lost the ability to see.</li>
<li>Cave-dwelling tetras have asymmetrical skulls with more sensory receptors on one side than the other.</li>
<li>These receptors help cave-dwelling tetras navigate in darkness.</li>
</ul>
<p>The student wants to emphasize a difference between surface-dwelling and cave-dwelling tetras. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #185 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • A lever is a simple machine consisting of a rigid beam and a fulcrum. • The fulcrum is the point about which the beam pivots. • The input force (effort) is the force applied to the lever. • The output force (load) is the force that the lever exerts on another object. • In first-class levers, the fulcrum is located between the effort and the load. • In second-class levers, the load is located between the effort and the fulcrum. The student wants to contrast first-class levers and second-class levers. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) In levers, the effort is the force applied to the lever; the load, in contrast, is the force that the lever exerts on another object.
(B) In first-class and second-class levers, the fulcrum and the load are in different locations.
(C) First-class levers are simple machines consisting of a rigid beam and a fulcrum, but then again, the same is true of second-class levers.
(D) In first-class levers, the fulcrum is located between the effort and the load, but in second-class levers, the load is located between the effort and the fulcrum.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Minnesota defines a lake as an inland body of water of at least 10 acres.
Wisconsin’s definition of a lake doesn’t take size into account.
By its own definition, Wisconsin has over 15,000 lakes, many smaller than 10 acres.
By Minnesota’s definition, Wisconsin has only about 6,000 lakes.
The student wants to contrast Minnesota’s definition of a lake with Wisconsin’s. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Wisconsin, which doesn’t take size into account in defining a lake, claims that it has over 15,000 lakes.
(B) Because its definition of a lake is different from Minnesota’s, it is unclear how many lakes Wisconsin really has.
(C) According to Minnesota’s definition of a lake—an inland body of water of at least 10 acres—Wisconsin has about 6,000 lakes.
(D) Minnesota’s definition of a lake—an inland body of water of at least 10 acres—is more restrictive than Wisconsin’s, which doesn’t take size into account.
Suggested correct answer: D
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Minnesota defines a lake as an inland body of water of at least 10 acres.</li>
<li>Wisconsin’s definition of a lake doesn’t take size into account.</li>
<li>By its own definition, Wisconsin has over 15,000 lakes, many smaller than 10 acres.</li>
<li>By Minnesota’s definition, Wisconsin has only about 6,000 lakes.</li>
</ul>
<p>The student wants to contrast Minnesota’s definition of a lake with Wisconsin’s. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #184 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • In astronomy, the mass of stars can be described in units called solar masses. • One solar mass is roughly equal to the mass of the Sun. • The mass of the star Proxima Centauri is 0.122 solar masses. • The mass of the star Sirius A is 2.063 solar masses. The student wants to emphasize the mass of Sirius A. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The mass of stars, like Proxima Centauri, can be described in units called solar masses.
(B) In astronomy, the mass of stars can be described in units called solar masses, and one solar mass is roughly equal to the mass of the Sun.
(C) The Sun is more massive than Proxima Centauri, which has a mass of 0.122 solar masses.
(D) With a mass of 2.063 solar masses, Sirius A is more massive than the Sun.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.61; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Seven species of sea turtle exist today.
Five sea turtle species can be found in the Atlantic Ocean.
One of those species is the Kemp’s ridley sea turtle.
Its scientific name is Lepidochelys kempii .
Another of those species is the olive ridley sea turtle.
Its scientific name is Lepidochelys olivacea .
The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Among the seven species of sea turtle is the olive ridley sea turtle, which can be found in the Atlantic Ocean.
(B) The Kemp’s ridley sea turtle is referred to as Lepidochelys kempii , while the olive ridley sea turtle is referred to as Lepidochelys olivacea .
(C) Both the Kemp’s ridley sea turtle and the olive ridley sea turtle can be found in the Atlantic Ocean.
(D) The Kemp’s ridley sea turtle (Lepidochelys kempii ) and the olive ridley sea turtle (Lepidochelys olivacea ) are different species.
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Seven species of sea turtle exist today.</li>
<li>Five sea turtle species can be found in the Atlantic Ocean.</li>
<li>One of those species is the Kemp’s ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys kempii</em>.</li>
<li>Another of those species is the olive ridley sea turtle.</li>
<li>Its scientific name is <em>Lepidochelys olivacea</em>.</li>
</ul>
<p>The student wants to emphasize a similarity between the two sea turtle species. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #183 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Iranian scholar Abu Rayhan al-Biruni studied Earth’s physical features. • He theorized that a large landmass existed west of Europe and east of Asia. • Al-Biruni published his landmass theory in 1037 CE. The student wants to specify when al-Biruni published his landmass theory. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) In 1037 CE, al-Biruni published his theory that a large landmass existed west of Europe and east of Asia.
(B) Al-Biruni, who studied Earth’s physical features, published a theory about a large landmass.
(C) Al-Biruni was an Iranian scholar who studied Earth’s physical features.
(D) An Iranian scholar who studied Earth’s physical features, al-Biruni theorized that a large landmass existed west of Europe and east of Asia.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.
Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.
Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.
At the time, Abele was not formally credited with designing the buildings.
Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.
The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Given that most of the buildings on Duke’s campus feature architectural styles that Abele had studied in Europe, historians believe Abele is the one who designed them.
(B) Though Abele wasn’t formally credited at the time, historians believe he designed most of the buildings on Duke’s campus.
(C) Most of Duke’s campus buildings, which were designed by a firm Abele worked for, were designed in the Gregorian and neo-Gothic architectural styles.
(D) Abele, an architect who studied Gregorian and neo-Gothic architecture in Europe, is believed to have designed most of the buildings on Duke’s campus.
Suggested correct answer: A
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Architect Julian Abele studied Gregorian and neo-Gothic architecture in Europe.</li>
<li>Abele worked for an architecture firm that was hired in 1924 to design buildings for Duke University’s new campus.</li>
<li>Most of the buildings on Duke’s campus were designed in the Gregorian or neo-Gothic architectural styles.</li>
<li>At the time, Abele was not formally credited with designing the buildings.</li>
<li>Based on the buildings’ architectural styles, historians believe Abele designed most of the campus buildings.</li>
</ul>
<p>The student wants to specify why historians believe Abele designed most of Duke’s campus buildings. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #182 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In retrospect, one of the lessons of the 2003 Human Genome Project is that a gene is affected by many factors, not the least of which is its interactions with the protein products of other genes. _______ rather than just focusing on the human genome, efforts to better understand gene mutations related to disease have begun to consider the human proteome, the complete set of proteins expressed by human genes. Which choice completes the text with the most logical transition?
(A) In other words,
(B) That said,
(C) For example,
(D) Accordingly,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.49
Bank-match candidate (unverified) A potter choosing which type of clay to use for a piece considers two key factors: the desired look of the piece and its intended use. ______ blank earthenware clay is often used for decorative pieces because of its rustic look. This type of clay is not often used in industrial settings, though, because it is less durable than other clays.
Which choice completes the text with the most logical transition?
Suggested correct answer: D
Verified stem text <p>A potter choosing which type of clay to use for a piece considers two key factors: the desired look of the piece and its intended use. <span>______</span><span class="sr-only">blank</span> earthenware clay is often used for decorative pieces because of its rustic look. This type of clay is not often used in industrial settings, though, because it is less durable than other clays.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #180 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) In 2014, Nestor Gomez won his first-ever storytelling competition, relating a tale about his life as a Guatemalan immigrant living in Chicago. _______ in 2017, Gomez created the show 80 Minutes Around the World as a platform for others to share stories about their immigration experiences. Which choice completes the text with the most logical transition?
(A) Instead,
(B) For example,
(C) Later,
(D) In other words,
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) As a young historian in the 1950s, Alixa Naff began interviewing fellow Arab American immigrants about their experiences straddling two cultures. Over the next few decades, Naff conducted more than 450 such interviews, also known as oral histories. ______ blank she collected photographs and other artifacts that represented her subjects’ experiences.
Which choice completes the text with the most logical transition?
Suggested correct answer: C
Verified stem text <p>As a young historian in the 1950s, Alixa Naff began interviewing fellow Arab American immigrants about their experiences straddling two cultures. Over the next few decades, Naff conducted more than 450 such interviews, also known as oral histories. <span>______</span><span class="sr-only">blank</span> she collected photographs and other artifacts that represented her subjects’ experiences.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #178 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #176 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Fans of the film Moana (2016) may not know that the deep and humorous voice behind the _______ belongs to comedian, actor, and musician Jemaine Clement. The versatile performer has appeared in everything from television commercials to action movies, but voice acting, specifically, has become a notable part of his career. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) character Tamatoa the crab
(B) character Tamatoa the crab,
(C) character: Tamatoa the crab,
(D) character, Tamatoa the crab
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.50
Bank-match candidate (unverified) Earth is not a perfect sphere. Due to the ______ blank gravitational pull, Earth bulges out on the sides closest to and farthest from the Moon. This distorting pull is known as a tidal force, and it is responsible for the changes in water levels that are called high and low tides.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: A
Verified stem text <p>Earth is not a perfect sphere. Due to the <span>______</span><span class="sr-only">blank</span> gravitational pull, Earth bulges out on the sides closest to and farthest from the Moon. This distorting pull is known as a tidal force, and it is responsible for the changes in water levels that are called high and low tides.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #169 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Simulated Change in Annual Aquifer Input and Irrigation Output if Precipitation Concentration Increases as Climate Models Predict
% change in surface % change in Baseline concentration of % change in water water used for groundwater used annual precipitation entering aquifers irrigation for irrigation Precipitation is currently somewhat concentrated 4.9 0.4 0.9 Precipitation is currently evenly distributed 11.0 9.0 7.9
Some climate models for the western United States predict that while total annual precipitation may remain unchanged from the present level, precipitation will become concentrated into fewer but more intense rain and snow events. University of Texas climate scientist Geeta Persad and her colleagues simulated how the amount of water entering aquifers and the amount being used for irrigation purposes would change if this were to occur. Persad and her colleagues concluded that concentration of precipitation into fewer events would result in a higher number of dry days, triggering more irrigation, but that this change in irrigation output is highly sensitive to the baseline concentration of precipitation that currently exists in an area. Which choice best describes data from the table that support Persad and her colleagues’ conclusion?
(A) If baseline precipitation is somewhat concentrated, the amount of water being used for irrigation will increase 0.4% for surface water and 0.9% for groundwater, whereas the amount of water entering aquifers will increase 11.0% if baseline precipitation is evenly distributed.
(B) If baseline precipitation is somewhat concentrated, water use for irrigation will increase only slightly, whereas it will increase 9.0% for surface water and 7.9% for groundwater if baseline precipitation is evenly distributed.
(C) If baseline precipitation is somewhat concentrated, the amount of water entering aquifers will increase 4.9%, while the amount being used for irrigation will increase 0.4% for surface water and 0.9% for groundwater.
(D) If baseline precipitation is somewhat concentrated, water use for irrigation will decline by a small amount, whereas it will increase 11.0% for surface water and 9.0% for groundwater if baseline precipitation is evenly distributed.
Corrected stem text Simulated Change in Annual Aquifer Input and Irrigation Output if Precipitation Concentration Increases as Climate Models Predict
§IMG§/full-test-images/test-5-rw-2-16-inline-0.png§% change in surface % change in Baseline concentration of % change in water water used for groundwater used §U§annual precipitation entering aquifers irrigation for irrigation§ Precipitation is currently §U§somewhat concentrated 4.9 0.4 0.9§ Precipitation is currently §U§evenly distributed 11.0 9.0 7.9§
Some climate models for the western United States predict that while total annual precipitation may remain unchanged from the present level, precipitation will become concentrated into fewer but more intense rain and snow events. University of Texas climate scientist Geeta Persad and her colleagues simulated how the amount of water entering aquifers and the amount being used for irrigation purposes would change if this were to occur. Persad and her colleagues concluded that concentration of precipitation into fewer events would result in a higher number of dry days, triggering more irrigation, but that this change in irrigation output is highly sensitive to the baseline concentration of precipitation that currently exists in an area. Which choice best describes data from the table that support Persad and her colleagues’ conclusion? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #167 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Climate scenario
Inés Ibáñez and colleagues studied a forest site in which some sugar maple trees receive periodic fertilization with nitrogen to mimic the broader trend of increasing anthropogenic nitrogen deposition in soil. Ibáñez and colleagues modeled the radial growth of the trees with and without nitrogen fertilization under three different climate scenarios (the current climate, moderate change, and extreme change). Although they found that climate change would negatively affect growth, they concluded that anthropogenic nitrogen deposition could more than offset that effect provided that change is moderate rather than extreme. Which choice best describes data from the graph that support Ibáñez and colleagues’ conclusion?
(A) Growth with nitrogen under the current climate exceeded growth with nitrogen under moderate change, but the latter exceeded growth without nitrogen under extreme change.
(B) Growth without nitrogen under the current climate exceeded growth without nitrogen under moderate change, but the latter exceeded growth with nitrogen under extreme change.
(C) C) Growth with nitrogen under moderate change exceeded growth without nitrogen under moderate change, but the latter exceeded growth without nitrogen under extreme change.
(D) D) Growth with nitrogen under moderate change exceeded growth without nitrogen under the current climate, but the latter exceeded growth with nitrogen under extreme change.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.50
Bank-match candidate (unverified)
90 80 70 60 50 40 30 20 10 0 Percentage of all sites analyzed 0% Up to 25% More than 25% Home Heating Needs Met with Subsurface Thermal Pollution for Two Temperature Conditions, by Percentage of Sites Local heating needs met Current surface temperature Maximum plausible surface , temperature
Urbanization, industrialization, and the warming climate create thermal pollution (excess heat) in the shallow subsurface soil. Susanne A. Benz and colleagues analyzed thousands of sites on three continents under one scenario in which surface temperature remains at the current level and under another in which the surface reaches the maximum plausible temperature. They then categorized each site according to the percentage of local home heating needs that could be met using this excess subsurface heat. The team concluded that if surface temperature approaches the maximum plausible level, the percentage of sites where thermal pollution could feasibly contribute to meeting home heating needs will increase.
Which choice best describes data in the graph that support Benz and colleagues’ conclusion?
(A) Under both temperature conditions, less than 10% of sites were in the up-to-25% group, but at the maximum plausible surface temperature, almost 80% of sites could have all their local heating needs met by thermal pollution.
(B) At current surface temperatures, more than 80% of the sites have no need for supplemental local home heating from subsurface thermal pollution, but at the maximum plausible surface temperature, more than 70% of sites exhibit significantly greater home heating needs.
(C) At current surface temperatures, more than 80% of sites can meet, at most, 25% of local home heating needs with subsurface thermal pollution, but at the maximum plausible surface temperature, more than 80% of sites can meet greater than 25% of local home heating needs.
(D) At current surface temperatures, more than 80% of the sites cannot use subsurface thermal pollution to meet any portion of local home heating needs, but at the maximum plausible surface temperature, that percentage drops below 20%.
Suggested correct answer: D
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<p>Urbanization, industrialization, and the warming climate create thermal pollution (excess heat) in the shallow subsurface soil. Susanne A. Benz and colleagues analyzed thousands of sites on three continents under one scenario in which surface temperature remains at the current level and under another in which the surface reaches the maximum plausible temperature. They then categorized each site according to the percentage of local home heating needs that could be met using this excess subsurface heat. The team concluded that if surface temperature approaches the maximum plausible level, the percentage of sites where thermal pollution could feasibly contribute to meeting home heating needs will increase.</p>
<p>Which choice best describes data in the graph that support Benz and colleagues’ conclusion?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #165 · Full test · rw · type: mcq
Source PDF page (reference) Question #162 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #161 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Text 1 Graphic novels are increasingly popular in bookstores and libraries, but they shouldn’t be classified as literature. By definition, literature tells a story or conveys meaning through language only; graphic novels tell stories through illustrations and use language only sparingly, in captions and dialogue. Graphic novels are experienced as series of images and not as language, making them more similar to film than to literature. Text 2 Graphic novels present their stories through both language and images. Without captions and dialogue, readers would be unable to understand what is depicted in the illustrations: the story results from the interaction of text and image. Moreover, Alison Bechdel’s FunHome and many other graphic novels feature text that is as beautifully written as the prose found in many standard novels. Therefore, graphic novels qualify as literary texts. Based on the texts, how would the author of Text 2 most likely respond to the overall argument presented in Text 1?
(A) By asserting that language plays a more important role in graphic novels than the author of Text 1 recognizes
(B) By acknowledging that the author of Text 1 has identified a flaw that is common to all graphic novels
(C) By suggesting that the story lines of certain graphic novels are more difficult to understand than the author of Text 1 claims
(D) By agreeing with the author of Text 1 that most graphic novels aren’t as well crafted as most literary works are
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.50
Bank-match candidate (unverified) Text 1
Like the work of Ralph Ellison before her, Toni Morrison’s novels feature scenes in which characters deliver sermons of such length and verbal dexterity that for a time, the text exchanges the formal parameters of fiction for those of oral literature. Given the many other echoes of Ellison in Morrison’s novels, both in structure and prose style, these scenes suggest Ellison’s direct influence on Morrison.
Text 2
In their destabilizing effect on literary form, the sermons in Morrison’s works recall those in Ellison’s. Yet literature by Black Americans abounds in moments where interpolated speech erodes the division between oral and written forms that literature in English has traditionally observed. Morrison’s use of the sermon is attributable not only to the influence of Ellison but also to a community-wide strategy of resistance to externally imposed literary conventions.
Based on the texts, how would the author of Text 2 most likely characterize the underlined claim in Text 1?
(A) As failing to consider Ellison’s and Morrison’s equivalent uses of the sermon within the wider cultural context in which they wrote
(B) As misunderstanding the function of sermons in novels by Black American writers other than Ellison and Morrison
(C) As disregarding points of structural and stylistic divergence between the works of Ellison and those of Morrison
(D) As being indebted to the tradition of resisting literary conventions that privilege written forms, such as novels, over sermons and other oral forms
Suggested correct answer: A
Verified stem text <p>Text 1</p>
<p>Like the work of Ralph Ellison before her, Toni Morrison’s novels feature scenes in which characters deliver sermons of such length and verbal dexterity that for a time, the text exchanges the formal parameters of fiction for those of oral literature. Given the many other echoes of Ellison in Morrison’s novels, both in structure and prose style, <span style="text-decoration: underline;">these scenes suggest Ellison’s direct influence on Morrison.</span></p>
<p>Text 2</p>
<p>In their destabilizing effect on literary form, the sermons in Morrison’s works recall those in Ellison’s. Yet literature by Black Americans abounds in moments where interpolated speech erodes the division between oral and written forms that literature in English has traditionally observed. Morrison’s use of the sermon is attributable not only to the influence of Ellison but also to a community-wide strategy of resistance to externally imposed literary conventions.</p>
<p>Based on the texts, how would the author of Text 2 most likely characterize the underlined claim in Text 1?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #154 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #153 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • The US Fish and Wildlife Service (FWS) keeps a list of all at-risk species. • Species on the list are classified as either endangered or threatened. • A species that is in danger of extinction throughout most or all of its range is classified as endangered. • A species that is likely to soon become endangered is classified as threatened. • The California red-legged frog (Ranadraytonii) is likely to soon become endangered, according to the FWS. The student wants to indicate the California red-legged frog’s FWS classification category. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Species on the FWS list, which includes the California red-legged frog (Ranadraytonii), are classified as either endangered or threatened.
(B) The California red-legged frog (Ranadraytonii) appears on the FWS list of at-risk species.
(C) According to the FWS, the California red-legged frog is in the endangered category, in danger of extinction throughout most or all of its range.
(D) Likely to soon become endangered, the California red-legged frog is classified as threatened by the FWS.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Roughly 96% of Australia’s estimated 200,000 animal species are invertebrates.
Invertebrates of the order Hymenoptera, which consists of sawflies, wasps, bees, and ants, are estimated to total 14,800 species in Australia.
Invertebrates of the order Coleoptera, which consists of beetles and weevils, are estimated to total 28,200 species in Australia.
Some of these invertebrates’ populations are threatened by invasive bird and fish species.
The student wants to emphasize the different orders in which Australia’s invertebrate animals are classified. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) In Australia, 28,200 species are estimated to be beetles and weevils, both classified as invertebrates of the order Coleoptera.
(B) Among Australia’s many invertebrates, sawflies, wasps, bees, and ants belong to the order Hymenoptera, while beetles and weevils belong to the order Coleoptera.
(C) Many sawflies, wasps, bees, and ants of the order Hymenoptera are threatened by some of Australia’s invasive bird and fish species.
(D) The order Hymenoptera is estimated to make up 14,800 of Australia’s 200,000 animal species.
Suggested correct answer: B mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Roughly 96% of Australia’s estimated 200,000 animal species are invertebrates.</li>
<li>Invertebrates of the order Hymenoptera, which consists of sawflies, wasps, bees, and ants, are estimated to total 14,800 species in Australia.</li>
<li>Invertebrates of the order Coleoptera, which consists of beetles and weevils, are estimated to total 28,200 species in Australia.</li>
<li>Some of these invertebrates’ populations are threatened by invasive bird and fish species.</li>
</ul>
<p>The student wants to emphasize the different orders in which Australia’s invertebrate animals are classified. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #152 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Scientists have developed a “freeze-thaw” battery that can retain 92% of its charge after twelve weeks. • The battery contains molten salt (a type of salt that liquifies when heated and solidifies at room temperature). • When the salt is in a liquid state, energy flows through the battery. • When the salt is in a solid state, energy stops flowing and is stored in the battery. • The stored (frozen) energy can be used by reheating (thawing) the battery. The student wants to specify how the salt enables energy storage. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Scientists have developed a freeze-thaw battery that contains molten salt, which liquifies when heated and solidifies at room temperature.
(B) The stored energy in a freeze-thaw battery, which contains molten salt, can be used by reheating the battery.
(C) When the molten salt in a freeze-thaw battery solidifies at room temperature, energy stops flowing and can be stored in the battery.
(D) Molten salt allows a freeze-thaw battery to retain 92% of its charge after twelve weeks.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.58; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
The tundra is a type of environment characterized by especially harsh winter conditions.
Winter temperatures in the tundra average a frigid −30 negative 30 degrees Fahrenheit.
Animals that have adapted to these conditions can survive tundra winters.
During the tundra’s short growing season, average temperatures can reach a relatively mild 54 degrees Fahrenheit.
Around 1,700 different kinds of plants are able to grow in the tundra.
The student wants to emphasize how harsh the conditions can be in the tundra. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Winters in the tundra are especially harsh, with temperatures averaging a frigid −30 negative 30 degrees Fahrenheit.
(B) Animals that have adapted to harsh winter conditions can survive tundra winters.
(C) There are around 1,700 different kinds of plants that can live in the tundra, where average temperatures can reach a mild 54 degrees Fahrenheit.
(D) Along with animals that have adapted to the tundra’s conditions, around 1,700 different kinds of plants can live in the tundra.
Suggested correct answer: A mismatches stored answer "D" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>The tundra is a type of environment characterized by especially harsh winter conditions.</li>
<li>Winter temperatures in the tundra average a frigid <span>−30</span><span class="sr-only">negative 30</span> degrees Fahrenheit.</li>
<li>Animals that have adapted to these conditions can survive tundra winters.</li>
<li>During the tundra’s short growing season, average temperatures can reach a relatively mild 54 degrees Fahrenheit.</li>
<li>Around 1,700 different kinds of plants are able to grow in the tundra.</li>
</ul>
<p>The student wants to emphasize how harsh the conditions can be in the tundra. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #151 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • In 1859, the novel AdamBede was published in England. • According to the novel’s title page, the author’s name was George Eliot. • George Eliot was widely assumed to be a pseudonym. • A pseudonym is a fake name used to conceal an author’s identity. • A woman named Mary Ann Evans later revealed herself as the novel’s real author. The student wants to identify the real author of AdamBede. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) The real author of AdamBede was Mary Ann Evans, who published the novel using the pseudonym George Eliot.
(B) George Eliot, which AdamBede’s title page indicated was the name of the novel’s author, was widely assumed to be a pseudonym.
(C) The title page of the novel AdamBede indicated that the author’s name was George Eliot.
(D) A woman who had used a pseudonym to conceal her identity later revealed herself as the real author of AdamBede.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.60; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Bharati Mukherjee was an Indian-born author of novels and short stories.
She published the novel The Holder of the World in 1993.
A central character in the novel is a woman living in twentieth-century United States.
Another central character is a woman living in seventeenth-century India.
The student wants to introduce the novel The Holder of the World to an audience already familiar with Bharati Mukherjee. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) Bharati Mukherjee’s settings include both twentieth-century United States and seventeenth-century India.
(B) In addition to her novel The Holder of the World, which was published in 1993, Indian-born author Bharati Mukherjee wrote other novels and short stories.
(C) Bharati Mukherjee’s novel The Holder of the World centers around two women, one living in twentieth-century United States and the other in seventeenth-century India.
(D) The Holder of the World was not the only novel written by Indian-born author Bharati Mukherjee.
Suggested correct answer: C
Verified stem text <p> While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Bharati Mukherjee was an Indian-born author of novels and short stories.</li>
<li>She published the novel <em>The Holder of the World</em> in 1993.</li>
<li>A central character in the novel is a woman living in twentieth-century United States.</li>
<li>Another central character is a woman living in seventeenth-century India.</li>
</ul>
<p>The student wants to introduce the novel <em>The Holder of the World </em>to an audience already familiar with Bharati Mukherjee. Which choice most effectively uses relevant information from the notes to accomplish this goal? </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #150 · Full test · rw · type: mcqno answer key
Currently stored (rendered) A turtle shell appears external to the animal, protecting its body like armor. _______ the shell is often incorrectly assumed to be an exoskeleton, a rigid outer casing like that of a crustacean or an insect, when in fact it is an endoskeleton, a part of the turtle’s internal bone structure, more akin to a spine or a pair of ribs. Which choice completes the text with the most logical transition?
(A) That being said,
(B) However,
(C) For instance,
(D) Hence,
Corrected stem text A turtle shell appears external to the animal, protecting its body like armor. _______ the shell is often incorrectly assumed to be an exoskeleton, a rigid outer casing like that of a crustacean or an insect, when in fact it is an endoskeleton, a part of the turtle’s internal bone structure, more akin to a spine or a pair of ribs. Which choice completes the text with the most logical transition? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #147 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #142 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #141 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #139 · Full test · rw · type: mcqno answer key
Source PDF page (reference) Question #137 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The Younger Dryas was a period of extreme cooling from 11,700 to 12,900 years ago in the Northern Hemisphere. Some scientists argue that a comet fragment hitting Earth brought about the cooling. Others disagree, partly because there is no known crater from such an impact that dates to the beginning of the period. In 2015, a team led by Kurt Kjær detected a 19-mile-wide crater beneath a glacier in Greenland. The scientists who believe an impact caused the Younger Dryas claim that this discovery supports their view. However, Kjær’s team hasn’t yet been able to determine the age of the crater. Therefore, the team suggests that _______ Which choice most logically completes the text?
(A) it can’t be concluded that the impact that made the crater was connected to the beginning of the Younger Dryas.
(B) it can’t be determined whether a comet fragment could make a crater as large as 19 miles wide.
(C) scientists have ignored the possibility that something other than a comet fragment could have made the crater.
(D) the scientists who believe an impact caused the Younger Dryas have made incorrect assumptions about when the period began.
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.44
Bank-match candidate (unverified) In 2008 a complete set of ancient pessoi (glass game pieces) was uncovered from beneath a paving stone in modern-day Israel. Due to their small size, pessoi were easily misplaced, making a whole set a rare find. This has led some experts to suggest that the set may have been buried intentionally; however, without clear evidence, archaeologists are left to ______ blank what happened.
Which choice completes the text with the most logical and precise word or phrase?
Suggested correct answer: A
Verified stem text <p>In 2008 a complete set of ancient <em>pessoi </em>(glass game pieces) was uncovered from beneath a paving stone in modern-day Israel. Due to their small size, <em>pessoi</em> were easily misplaced, making a whole set a rare find. This has led some experts to suggest that the set may have been buried intentionally; however, without clear evidence, archaeologists are left to <span>______</span><span class="sr-only">blank</span> what happened.</p>
<p>Which choice completes the text with the most logical and precise word or phrase?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #136 · Full test · rw · type: mcq
Currently stored (rendered) The population of the coral Lophelia pertusa declined significantly around 9,000 years ago in the Alboran Sea and around 11,000 years ago near the Mauritanian coast. Using the ratio of manganese to calcium, which inversely correlates with ocean oxygenation levels, marine scientist Rodrigo da Costa Portilho-Ramos and colleagues evaluated whether oxygenation played a role in the declines of L. pertusa. The researchers concluded that oxygenation may have been important in the Alboran Sea but not near the Mauritanian coast, since _______ Which choice most effectively uses data from the graph to complete the statement?
(A) a substantial increase in oxygenation in the Alboran Sea corresponded with the local decline in L. pertusa, but the opposite relationship between oxygenation and L. pertusa was found near the Mauritanian coast.
(B) L. pertusa declined in the Alboran Sea during a period of substantial local decline in oxygenation, but L. pertusa declined near the Mauritanian coast during a period of little local change in oxygenation.
(C) C) oxygenation in the Alboran Sea was higher before the decline in L. pertusa than after the decline, whereas oxygenation near the Mauritanian coast was relatively low both before and after the decline in L. pertusa.
(D) oxygenation in the Alboran Sea tended to be substantially higher than oxygenation near the Mauritanian coast during the period studied.
Corrected stem text The population of the coral Lophelia pertusa declined significantly around 9,000 years ago in the Alboran Sea and around 11,000 years ago near the Mauritanian coast. Using the ratio of manganese to calcium, which inversely correlates with ocean oxygenation levels, marine scientist Rodrigo da Costa Portilho-Ramos and colleagues evaluated whether oxygenation played a role in the declines of L. pertusa. The researchers concluded that oxygenation may have been important in the Alboran Sea but not near the Mauritanian coast, since _______ §IMG§/full-test-images/test-5-rw-1-16-inline-0.png§ Which choice most effectively uses data from the graph to complete the statement? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #135 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) “The Yellow Wallpaper” is an 1892 short story by Charlotte Perkins Gilman. In the story, the narrator expresses mixed feelings about her surroundings: _______ Which quotation from “The Yellow Wallpaper” most effectively illustrates the claim?
(A) “This wallpaper has a kind of sub-pattern in a different shade, a particularly irritating one, for you can only see it in certain lights, and not clearly then.”
(B) “By moonlight—the moon shines in all night when there is a moon—I wouldn’t know it was the same paper.”
(C) “I’m really getting quite fond of the big room, all but that horrid [wall]paper.”
(D) “The color is repellant, almost revolting; a smouldering, unclean yellow, strangely faded by the slow-turning sunlight.”
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.59; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) “The Rock and the Sea” is an 1893 poem by Charlotte Perkins Gilman. In the poem, a rock is portrayed as intending to confront and restrain the sea: ______ blank
Which quotation from “The Rock and the Sea” most effectively illustrates the claim?
(A) “I am the Rock. Black midnight falls; / The terrible breakers rise like walls; / With curling lips and gleaming teeth / They plunge and tear at my bones beneath.”
(B) “I am the Sea. I hold the land / As one holds an apple in his hand, / Hold it fast with sleepless eyes, / Watching the continents sink and rise.”
(C) “I am the Rock, presumptuous Sea! / I am set to encounter thee. / Angry and loud or gentle and still, / I am set here to limit thy power, and I will!”
(D) “I am the Sea. The earth I sway; / Granite to me is potter’s clay; / Under the touch of my careless waves / It rises in turrets and sinks in caves.”
Suggested correct answer: C mismatches stored answer "B" -- double check
Verified stem text <p>“The Rock and the Sea” is an 1893 poem by Charlotte Perkins Gilman. In the poem, a rock is portrayed as intending to confront and restrain the sea: <span>______</span><span class="sr-only">blank</span></p>
<p>Which quotation from “The Rock and the Sea” most effectively illustrates the claim?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #134 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Partial List of Candidate Species for De-extinction Common name Scientific name Became extinct Heteralocha Huia acutirostris 1907 Caribbean Monachus monk seal tropicalis 1952 Passenger Ectopistes pigeon migratorius 1914 Saber-toothed 11,000 years cat Smilodon before present Woolly Mammuthus 6,400 years mammoth primigenius before present
The passage of time is among the many obstacles faced by scientists who are pursuing de-extinction efforts—that is, efforts to use breeding or a mixture of cloning and genetic engineering to bring back extinct species. Specifically, researchers are concerned that the longer a species has been extinct, the less likely it is that a suitable habitat still exists for that species. Among candidate species for de-extinction, this problem would be especially concerning for the _______ Which choice most effectively uses data from the table to complete the statement?
(A) passenger pigeon (Ectopistes migratorius), which became extinct only a few years after the huia (Heteralocha acutirostris).
(B) saber-toothed cat (Smilodon), which became extinct 11,000 years ago.
(C) woolly mammoth (Mammuthus primigenius), which became extinct several thousand years before the saber-toothed cat (Smilodon).
(D) Caribbean monk seal (Monachus tropicalis), which became extinct in 1952.
Corrected stem text §U§Partial List of Candidate Species for De-extinction§ §U§Common name Scientific name Became extinct§ Heteralocha §U§Huia acutirostris 1907§ Caribbean Monachus §IMG§/full-test-images/test-5-rw-1-14-inline-0.png§monk seal tropicalis 1952 Passenger Ectopistes §U§pigeon migratorius 1914§ Saber-toothed 11,000 years §U§cat Smilodon before present§ Woolly Mammuthus 6,400 years §U§mammoth primigenius before present§
The passage of time is among the many obstacles faced by scientists who are pursuing de-extinction efforts—that is, efforts to use breeding or a mixture of cloning and genetic engineering to bring back extinct species. Specifically, researchers are concerned that the longer a species has been extinct, the less likely it is that a suitable habitat still exists for that species. Among candidate species for de-extinction, this problem would be especially concerning for the _______ Which choice most effectively uses data from the table to complete the statement? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #132 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The ancient writing system used in the Maya kingdoms of southern Mexico and Central America had a symbol for the number zero. The earliest known example of the symbol dates to more than 2,000 years ago. At that time, almost none of the writing systems elsewhere in the world possessed a zero symbol. And the use of zero in Mexico and Central America may be even more ancient. Some historians suggest that Maya mathematicians inherited it from the Olmec civilization, which flourished in the region 2,400–3,600 years ago. According to the text, what do some historians suggest about Maya civilization?
(A) Maya civilization acquired the use of zero from the Olmec civilization.
(B) Maya civilization respected its historians more than it respected its mathematicians.
(C) Maya civilization was highly secretive about its intellectual achievements.
(D) Maya civilization tried to introduce its writing system to other civilizations.
Corrected stem text The ancient writing system used in the Maya kingdoms of southern Mexico and Central America had a symbol for the number zero. The earliest known example of the symbol dates to more than 2,000 years ago. At that time, almost none of the writing systems elsewhere in the world possessed a zero symbol. And the use of zero in Mexico and Central America may be even more ancient. Some historians suggest that Maya mathematicians inherited it from the Olmec civilization, which flourished in the region 2,400–3,600 years ago. According to the text, what do some historians suggest about Maya civilization? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #130 · Full test · rw · type: mcqno answer key
Currently stored (rendered) Changes to vegetation cover and other human activities influence carbon and nitrogen levels in soil, though how deep these effects extend is unclear. Hypothesizing that differences in land use lead to differences in carbon and nitrogen levels that are not restricted to the topsoil layer (0–30 cm deep), Chukwuebuka Okolo and colleagues sampled soils across multiple land-use types (e.g., grazing land, cropland, forest) within each of several Ethiopian locations. They found, though, that across land-use types, carbon and nitrogen decreased to comparably low levels beyond depths of 30 cm. Which choice best describes the overall structure of the text?
(A) It describes a phenomenon that scientists do not fully understand, explains a research team’s hypothesis about that phenomenon, and then describes a finding that led the team to refine the hypothesis.
(B) It introduces an unresolved scientific question, presents a research team’s hypothesis pertaining to that question, and then describes an observation made by the team that conflicts with that hypothesis.
(C) It discusses a process that scientists are somewhat unclear about, introduces competing hypotheses about that process, and then explains how a research team concluded that one of those hypotheses is likely correct.
(D) It explains a hypothesis that has been the subject of scientific debate, discusses how a research team tested that hypothesis, and then presents data the team collected that validate the hypothesis.
Corrected stem text Changes to vegetation cover and other human activities influence carbon and nitrogen levels in soil, though how deep these effects extend is unclear. Hypothesizing that differences in land use lead to differences in carbon and nitrogen levels that are not restricted to the topsoil layer (0–30 cm deep), Chukwuebuka Okolo and colleagues sampled soils across multiple land-use types (e.g., grazing land, cropland, forest) within each of several Ethiopian locations. They found, though, that across land-use types, carbon and nitrogen decreased to comparably low levels beyond depths of 30 cm. Which choice best describes the overall structure of the text? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #124 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #123 · Full test · rw · type: mcqBank-match candidate available
Source PDF page (reference) Question #121 · Full test · rw · type: mcqno answer key
Currently stored (rendered) The following text is from the 1913 story “The King’s Coin” by Emily Pauline Johnson, a Kanienkahagen (Mohawk) writer also known as Tekahionwake. Fox-Foot, a young Ojibwe man, is guiding a group of fur traders who are traveling by canoe and suspects that they are being followed. At supper time, Fox-Foot would allow no fire to be built, no landing to be made, no trace of their passing to be left. They ate canned meat and marmalade, drank again of the stream and pushed on, until just at dusk they reached the edge of a long, still lake, with shores of granite and dense fir forest. As used in the text, what does the word “trace” most nearly mean?
(A) Evidence
(B) Blemish
(C) Amount
(D) Sketch
Corrected stem text The following text is from the 1913 story “The King’s Coin” by Emily Pauline Johnson, a Kanienkahagen (Mohawk) writer also known as Tekahionwake. Fox-Foot, a young Ojibwe man, is guiding a group of fur traders who are traveling by canoe and suspects that they are being followed. At supper time, Fox-Foot would allow no fire to be built, no landing to be made, no §U§trace§of their passing to be left. They ate canned meat and marmalade, drank again of the stream and pushed on, until just at dusk they reached the edge of a long, still lake, with shores of granite and dense fir forest. As used in the text, what does the word “trace” most nearly mean? Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Save & unflag Source PDF page (reference) Question #118 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The equation x 2 {}^{2} 2 + (y − 1)2 {}^{2} 2 = 49 represents circle A. Circle B is obtained by shifting circle A down 2 units in the xy-plane. Which of the following equations represents circle B?
(A) (x − 2)2 {}^{2} 2 + (y − 1)2 {}^{2} 2 = 49
(B) x 2 {}^{2} 2 + (y − 3)2 {}^{2} 2 = 49
(C) (x + 2)2 {}^{2} 2 + (y − 1)2 {}^{2} 2 = 49
(D) x 2 {}^{2} 2 + (y + 1)2 {}^{2} 2 = 49
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.94; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The equation x 2 + ( y − 1 ) 2 = 49 x^{2} + \left(y - 1\right)^{2} = 49 x 2 + ( y − 1 ) 2 = 49 represents circle A. Circle B is obtained by shifting circle A down 2 2 2 units in the xy -plane. Which of the following equations represents circle B?
(A) ( x − 2 ) 2 + ( y − 1 ) 2 = 49 \left(x - 2\right)^{2} + \left(y - 1\right)^{2} = 49 ( x − 2 ) 2 + ( y − 1 ) 2 = 49
(B) x 2 + ( y − 3 ) 2 = 49 x^{2} + \left(y - 3\right)^{2} = 49 x 2 + ( y − 3 ) 2 = 49
(C) ( x + 2 ) 2 + ( y − 1 ) 2 = 49 \left(x + 2\right)^{2} + \left(y - 1\right)^{2} = 49 ( x + 2 ) 2 + ( y − 1 ) 2 = 49
(D) x 2 + ( y + 1 ) 2 = 49 x^{2} + \left(y + 1\right)^{2} = 49 x 2 + ( y + 1 ) 2 = 49
Suggested correct answer: D
Verified stem text <p style="text-align: left;">The equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mi>x</mi><mn>2</mn></msup><mo>+</mo><msup><mrow><mo fence="true">(</mo><mi>y</mi><mo>−</mo><mn>1</mn><mo fence="true">)</mo></mrow><mn>2</mn></msup><mo>=</mo><mn>49</mn></mrow><annotation encoding="application/x-tex">x^{2} + \left(y - 1\right)^{2} = 49</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8974em;vertical-align:-0.0833em;"></span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8141em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.204em;vertical-align:-0.25em;"></span><span class="minner"><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mord">1</span><span class="mclose delimcenter" style="top:0em;">)</span></span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.954em;"><span style="top:-3.2029em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">2</span></span></span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">49</span></span></span></span> represents circle A. Circle B is obtained by shifting circle A down <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2</mn></mrow><annotation encoding="application/x-tex">2</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">2</span></span></span></span> units in the <em>xy</em>-plane. Which of the following equations represents circle B?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #115 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) If a new graph of three linear equations is created using the system of equations shown and the equation x + 4y = −16, how many solutions (xy, ) will the resulting system of three equations have?
(A) Zero
(B) Exactly one
(C) Exactly two
(D) Infinitely many
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.65
Bank-match candidate (unverified)
For the first line in the system:
The line slants gradually down from left to right.
The line passes through the following points:
(negative 4 comma 5)
(0 comma 4)
(8 comma 2)
For the second line in the system:
The line is horizontal.
The line passes through the following points:
If a new graph of three linear equations is created using the system of equations shown and the equation x + 4 y = − 16 x + 4 y = - 16 x + 4 y = − 16 , how many solutions ( x , y ) \left(x , y\right) ( x , y ) will the resulting system of three equations have?
Suggested correct answer: A
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<div role="region" aria-label="Long description for graph of a system of 2 lines" class="sr-only"><ul>
<li>For the first line in the system:
<ul>
<li>The line slants gradually down from left to right.</li>
<li>The line passes through the following points:
<ul>
<li>(negative 4 comma 5)</li>
<li>(0 comma 4)</li>
<li>(8 comma 2)</li>
</ul>
</li>
</ul>
</li>
<li>For the second line in the system:
<ul>
<li>The line is horizontal.</li>
<li>The line passes through the following points:
<ul>
<li>(0 comma 2)</li>
<li>(8 comma 2)</li>
</ul>
</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">If a new graph of three linear equations is created using the system of equations shown and the equation <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>+</mo><mn>4</mn><mi>y</mi><mo>=</mo><mo>−</mo><mn>16</mn></mrow><annotation encoding="application/x-tex">x + 4 y = - 16</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">4</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.7278em;vertical-align:-0.0833em;"></span><span class="mord">−</span><span class="mord">16</span></span></span></span>, how many solutions <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mi>x</mi><mo separator="true">,</mo><mi>y</mi><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(x , y\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord mathnormal">x</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> will the resulting system of three equations have?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #113 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #109 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) In the figure, lines m and n are parallel. If x = 6k + 13 and y = 8k − 29, what is the value of z ?
(A) 3
(B) 21
(C) 41
(D) 139
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.77; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
In the figure above, lines m m m and n n n are parallel. What is the value of b b b ?
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <div class="stimulus_reference ">
<div class="standalone_image ">
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" alt="The figure presents 5 lines labeled j, k, l, m, and n. Lines m and n are horizontal and line m lies above line n. Line j is slanted downward and to the right, and line k is slanted upward and to the right. Lines j, k, and top horizontal line m intersect, forming six angles. The angle below line m and to the left of line k and the angle below line m and to the right of line j are both labeled, a, degrees. Line k intersects the bottom horizontal line n, forming four angles. The angle above line n and to the left of line k is labeled 130 degrees. Line l is vertical and intersects lines m and n on the right side of the figure. Line j, line l, and the bottom horizontal line n intersect, forming six angles. The angle, above line n, to the left of vertical line l, and to the right of line j is labeled b degrees. There is a right angle symbol at an angle formed by horizontal line m and vertical line l." /></div>
</div>
<p class="stem_paragraph ">In the figure above, lines <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>m</mi></mrow><annotation encoding="application/x-tex">m</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">m</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>n</mi></mrow><annotation encoding="application/x-tex">n</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">n</span></span></span></span> are parallel. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> ?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #106 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #99 · Full test · math · type: grid_inBank-match candidate available
Source PDF page (reference) Question #96 · Full test · math · type: mcqBank-match candidate available
Source PDF page (reference) Question #95 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) A fish swam a distance of 5,104 yards. How far did the fish swim, in miles? (1 mile = 1,760 yards)
(A) 0.3
(B) 2.9
(C) 3,344
(D) 6,864
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.88; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) A fish swam a distance of 5 , 104 5,104 5 , 104 yards. How far did the fish swim, in miles ? ( 1 mile = 1 , 760 yards ) \left(1 \text{mile} = 1,760 \text{yards}\right) ( 1 mile = 1 , 760 yards )
Suggested correct answer: B
Verified stem text <p style="text-align: left;">A fish swam a distance of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>5</mn><mo separator="true">,</mo><mn>104</mn></mrow><annotation encoding="application/x-tex">5,104</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8389em;vertical-align:-0.1944em;"></span><span class="mord">5</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">104</span></span></span></span> yards. How far did the fish swim, in <span style="text-decoration: underline;">miles</span>? <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">(</mo><mn>1</mn><mtext>mile</mtext><mo>=</mo><mn>1</mn><mo separator="true">,</mo><mn>760</mn><mtext>yards</mtext><mo fence="true">)</mo></mrow><annotation encoding="application/x-tex">\left(1 \text{mile} = 1,760 \text{yards}\right)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;">(</span><span class="mord">1</span><span class="mord text"><span class="mord">mile</span></span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mord">1</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.1667em;"></span><span class="mord">760</span><span class="mord text"><span class="mord">yards</span></span><span class="mclose delimcenter" style="top:0em;">)</span></span></span></span></span> </p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #94 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) 1 The line graph shows the estimated number of chipmunks in a state park on April 1 of each year from 1989 to 1999. Based on the line graph, in which year was the estimated number of chipmunks in the state park the greatest?
(A) 1989
(B) 1994
(C) 1995
(D) 1998
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.71; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The line graph shows the estimated number of chipmunks in a state park on April 1 1 1 of each year from 1989 1989 1989 to 1999 1999 1999 .
The line graph:
Begins at 1989, 38 chipmunks
Remains level to 1990, 38 chipmunks
Rises sharply to 1991, 98 chipmunks
Rises gradually to 1992, 101 chipmunks
Falls sharply to 1993, 53 chipmunks
Rises sharply to 1994, 158 chipmunks
Falls sharply to 1995, 48 chipmunks
Rises sharply to 1996, 98 chipmunks
Falls gradually to 1997, 93 chipmunks
Falls sharply to 1998, 53 chipmunks
Rises sharply to 1999, 113 chipmunks
Based on the line graph, in which year was the estimated number of chipmunks in the state park the greatest?
Suggested correct answer: B
Verified stem text <p style="text-align: left;">The line graph shows the estimated number of chipmunks in a state park on April <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1</mn></mrow><annotation encoding="application/x-tex">1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span> of each year from <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1989</mn></mrow><annotation encoding="application/x-tex">1989</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1989</span></span></span></span> to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>1999</mn></mrow><annotation encoding="application/x-tex">1999</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1999</span></span></span></span>.</p>
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d="M59.892,6.26a8.117,8.117,0,0,1,1.143-4.438,3.549,3.549,0,0,1,6.173-.01A8.175,8.175,0,0,1,68.341,6.26,8.128,8.128,0,0,1,67.2,10.7a3.523,3.523,0,0,1-6.154-.01A8.089,8.089,0,0,1,59.892,6.26Zm1.7-.02a10.06,10.06,0,0,0,.678,3.925q.678,1.6,1.745,1.6,1.239,0,1.928-1.609a10.238,10.238,0,0,0,.688-4.011A9.592,9.592,0,0,0,65.958,2.3Q65.278.757,64.213.756q-1.182,0-1.9,1.57A9.416,9.416,0,0,0,61.6,6.24Z"></path><path d="M69.271,6.26a8.117,8.117,0,0,1,1.144-4.438,3.548,3.548,0,0,1,6.172-.01A8.166,8.166,0,0,1,77.721,6.26,8.128,8.128,0,0,1,76.578,10.7a3.523,3.523,0,0,1-6.154-.01A8.089,8.089,0,0,1,69.271,6.26Zm1.706-.02a10.06,10.06,0,0,0,.678,3.925q.678,1.6,1.744,1.6,1.24,0,1.929-1.609a10.238,10.238,0,0,0,.688-4.011A9.574,9.574,0,0,0,75.337,2.3Q74.659.757,73.593.756q-1.182,0-1.9,1.57A9.416,9.416,0,0,0,70.977,6.24Z"></path><polyline points="87.815 112.59 115.178 112.59 142.541 73.416 169.904 71.455 197.267 102.922 224.63 34.255 251.993 106.079 279.447 73.416 306.72 76.685 334.083 102.836 361.448 63.61" fill="none" stroke="#202020" stroke-linecap="round" stroke-linejoin="round" stroke-width="2.835"></polyline></g></svg><div role="region" aria-label="Long description for line graph" class="sr-only"><ul>
<li>The line graph:<br />
<ul>
<li>Begins at 1989, 38 chipmunks</li>
<li>Remains level to 1990, 38 chipmunks</li>
<li>Rises sharply to 1991, 98 chipmunks </li>
<li>Rises gradually to 1992, 101 chipmunks</li>
<li>Falls sharply to 1993, 53 chipmunks</li>
<li>Rises sharply to 1994, 158 chipmunks </li>
<li>Falls sharply to 1995, 48 chipmunks </li>
<li>Rises sharply to 1996, 98 chipmunks </li>
<li>Falls gradually to 1997, 93 chipmunks</li>
<li>Falls sharply to 1998, 53 chipmunks </li>
<li>Rises sharply to 1999, 113 chipmunks</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">Based on the line graph, in which year was the estimated number of chipmunks in the state park the greatest?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #87 · Full test · math · type: grid_inBank-match candidate available
Currently stored (rendered) The expression 6 5 {}^{5} 5 35 {}^{5} 5 x 45 {}^{45} 45 ·8 {}^{8} 8 28 {}^{8} 8 x is equivalent to ax b {}^{b} b , where a and b are positive constants and x > 1. What is the value of a + b ?
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.87; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The expression 6 3 5 x 45 5 ⋅ 2 8 x 8 6 \sqrt[5]{3^{5} x^{45}} \cdot \sqrt[8]{2^{8} x} 6 5 3 5 x 45 ⋅ 8 2 8 x is equivalent to a x b a x^{b} a x b , where a a a and b b b are positive constants and x > 1 x > 1 x > 1 . What is the value of a + b a + b a + b ?
Suggested correct answer: 361/8 or 45.12 or 45.13 mismatches stored answer "3618" -- double check
Verified stem text <p style="text-align: left;">The expression <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>6</mn><mroot><mrow><msup><mn>3</mn><mn>5</mn></msup><msup><mi>x</mi><mn>45</mn></msup></mrow><mn>5</mn></mroot><mo>⋅</mo><mroot><mrow><msup><mn>2</mn><mn>8</mn></msup><mi>x</mi></mrow><mn>8</mn></mroot></mrow><annotation encoding="application/x-tex">6 \sqrt[5]{3^{5} x^{45}} \cdot \sqrt[8]{2^{8} x}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.0849em;"></span><span class="mord">6</span><span class="mord sqrt"><span class="root"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8443em;"><span style="top:-3.0221em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size6 size1 mtight"><span class="mord mtight"><span class="mord mtight">5</span></span></span></span></span></span></span></span><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9551em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord"><span class="mord">3</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.7401em;"><span style="top:-2.989em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">5</span></span></span></span></span></span></span></span></span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.7401em;"><span style="top:-2.989em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">45</span></span></span></span></span></span></span></span></span></span></span><span style="top:-2.9151em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.0849em;"><span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">⋅</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:1.04em;vertical-align:-0.0849em;"></span><span class="mord sqrt"><span class="root"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8443em;"><span style="top:-3.0221em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size6 size1 mtight"><span class="mord mtight"><span class="mord mtight">8</span></span></span></span></span></span></span></span><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9551em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord"><span class="mord">2</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.7401em;"><span style="top:-2.989em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight">8</span></span></span></span></span></span></span></span></span><span class="mord mathnormal">x</span></span></span><span style="top:-2.9151em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg xmlns="http://www.w3.org/2000/svg" width="400em" height="1.08em" viewBox="0 0 400000 1080" preserveAspectRatio="xMinYMin slice"><path d="M95,702
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c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
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s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
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M834 80h400000v40h-400000z"/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.0849em;"><span></span></span></span></span></span></span></span></span> is equivalent to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><msup><mi>x</mi><mi>b</mi></msup></mrow><annotation encoding="application/x-tex">a x^{b}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8491em;"></span><span class="mord mathnormal">a</span><span class="mord"><span class="mord mathnormal">x</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8491em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">b</span></span></span></span></span></span></span></span></span></span></span></span>, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi></mrow><annotation encoding="application/x-tex">a</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">a</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span> are positive constants and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mo>></mo><mn>1</mn></mrow><annotation encoding="application/x-tex">x > 1</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.5782em;vertical-align:-0.0391em;"></span><span class="mord mathnormal">x</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">></span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">1</span></span></span></span>. What is the value of <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>a</mi><mo>+</mo><mi>b</mi></mrow><annotation encoding="application/x-tex">a + b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6667em;vertical-align:-0.0833em;"></span><span class="mord mathnormal">a</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #78 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) What is an equation of the graph shown?
(A) y = −2x − 8
(B) y = x− 8
(C) y = −x − 8
(D) y = 2x − 8
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.62; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
Which of the following is an equation of the graph shown in the x y xy x y -plane above?
(A)
y = − 1 4 x − 1 y = -\dfrac{1}{4} x - 1 y = − 4 1 x − 1
(C)
y = − x − 1 4 y = -x - \dfrac{1}{4} y = − x − 4 1
(D)
y = − 4 x − 1 y = -4 x - 1 y = − 4 x − 1
Suggested correct answer: A mismatches stored answer "C" -- double check
Verified stem text <div class="stimulus_reference ">
<div class="passage ">
<div class="prose style:1 ">
<div class="standalone_image ">
<img 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" alt="The figure presents the graph of a line in the x y plane. The number 1 is indicated on both axes. The line passes through the point with coordinates negative 4 comma 0, and the point with coordinates 0 comma negative 1." /></div>
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<p class="stem_paragraph ">Which of the following is an equation of the graph shown in the <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi><mi>y</mi></mrow><annotation encoding="application/x-tex">xy</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">x</span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>-plane above?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #77 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) 2.5b + 5r = 80 The given equation describes the relationship between the number of birds, b, and the number of reptiles, r, that can be cared for at a pet care business on a given day. If the business cares for 16 reptiles on a given day, how many birds can it care for on this day?
(A) 0
(B) 5
(C) 40
(D) 80
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.97; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) 2.5 b + 5 r = 80 2.5 b + 5 r = 80 2.5 b + 5 r = 80
The given equation describes the relationship between the number of birds, b b b , and the number of reptiles, r r r , that can be cared for at a pet care business on a given day. If the business cares for 16 16 16 reptiles on a given day, how many birds can it care for on this day?
Suggested correct answer: A mismatches stored answer "B" -- double check
Verified stem text <p style="text-align: center;"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>2.5</mn><mi>b</mi><mo>+</mo><mn>5</mn><mi>r</mi><mo>=</mo><mn>80</mn></mrow><annotation encoding="application/x-tex">2.5 b + 5 r = 80</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.7778em;vertical-align:-0.0833em;"></span><span class="mord">2.5</span><span class="mord mathnormal">b</span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">5</span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span><span class="mspace" style="margin-right:0.2778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2778em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">80</span></span></span></span></p>
<p style="text-align: left;">The given equation describes the relationship between the number of birds, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>b</mi></mrow><annotation encoding="application/x-tex">b</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em;"></span><span class="mord mathnormal">b</span></span></span></span>, and the number of reptiles, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>r</mi></mrow><annotation encoding="application/x-tex">r</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal" style="margin-right:0.0278em;">r</span></span></span></span>, that can be cared for at a pet care business on a given day. If the business cares for <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>16</mn></mrow><annotation encoding="application/x-tex">16</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">16</span></span></span></span> reptiles on a given day, how many birds can it care for on this day?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #76 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The scatterplot shows the relationship between two variables, x and y. Which of the following equations is the most appropriate linear model for the data shown?
(A) y = 0.9 + 9.4x
(B) y = 0.9 − 9.4x
(C) y = 9.4 + 0.9x
(D) y = 9.4 − 0.9x
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.68; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The scatterplot shows the relationship between two variables, x x x and y y y .
The scatterplot has 10 data points.
The data points are in a linear pattern trending down from left to right.
The data points have the following approximate coordinates:
(0 comma 10)
(1.2 comma 9)
(2.3 comma 8)
(3.1 comma 5)
(4.8 comma 5)
(5.2 comma 3)
(6.5 comma 3)
(7.2 comma 3)
(9.6 comma 2)
(8.8 comma 1)
Which of the following equations is the most appropriate linear model for the data shown?
(A) y = 0.9 + 9.4 x y = 0.9 + 9.4 x y = 0.9 + 9.4 x
(B) y = 0.9 − 9.4 x y = 0.9 - 9.4 x y = 0.9 − 9.4 x
(C) y = 9.4 + 0.9 x y = 9.4 + 0.9 x y = 9.4 + 0.9 x
(D) y = 9.4 − 0.9 x y = 9.4 - 0.9 x y = 9.4 − 0.9 x
Suggested correct answer: D
Verified stem text <p style="text-align: left;">The scatterplot shows the relationship between two variables, <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>x</mi></mrow><annotation encoding="application/x-tex">x</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.4306em;"></span><span class="mord mathnormal">x</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>y</mi></mrow><annotation encoding="application/x-tex">y</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.625em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.0359em;">y</span></span></span></span>.</p>
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<div role="region" aria-label="Long description for scatterplot" class="sr-only"><ul>
<li>The scatterplot has 10 data points.</li>
<li>The data points are in a linear pattern trending down from left to right.</li>
<li>The data points have the following approximate coordinates:
<ul>
<li>(0 comma 10)</li>
<li>(1.2 comma 9)</li>
<li>(2.3 comma 8)</li>
<li>(3.1 comma 5)</li>
<li>(4.8 comma 5)</li>
<li>(5.2 comma 3)</li>
<li>(6.5 comma 3)</li>
<li>(7.2 comma 3)</li>
<li>(9.6 comma 2)</li>
<li>(8.8 comma 1)</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">Which of the following equations is the most appropriate linear model for the data shown?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #75 · Full test · math · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Right triangles PQR and STU are similar, where P corresponds to S. If the measure of angle Q is 18°, what is the measure of angle S ?
(A) 18°
(B) 72°
(C) 82°
(D) 162°
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.65; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified)
Right triangle upper P upper Q upper R is labeled as follows:
Angle upper R is a right angle.
Right triangle upper S upper T upper U is labeled as follows:
Angle upper U is a right angle.
A note indicates the figures are not drawn to scale.
Right triangles P Q R P Q R P QR and S T U S T U S T U are similar, where P P P corresponds to S S S . If the measure of angle Q Q Q is 18 ∘ 18^\circ 1 8 ∘ , what is the measure of angle S S S ?
Suggested correct answer: B
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role="region" aria-label="Long description for right triangles upper P upper Q upper R and upper S upper T upper U" class="sr-only"><ul>
<li>Right triangle upper P upper Q upper R is labeled as follows:
<ul>
<li>Angle upper R is a right angle.</li>
</ul>
</li>
<li>Right triangle upper S upper T upper U is labeled as follows:
<ul>
<li>Angle upper U is a right angle.</li>
</ul>
</li>
<li>A note indicates the figures are not drawn to scale.</li>
</ul></div><p></p>
<p style="text-align: left;">Right triangles <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi><mi>Q</mi><mi>R</mi></mrow><annotation encoding="application/x-tex">P Q R</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span><span class="mord mathnormal" style="margin-right:0.0077em;">QR</span></span></span></span> and <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>S</mi><mi>T</mi><mi>U</mi></mrow><annotation encoding="application/x-tex">S T U</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">S</span><span class="mord mathnormal" style="margin-right:0.1389em;">T</span><span class="mord mathnormal" style="margin-right:0.109em;">U</span></span></span></span> are similar, where <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>P</mi></mrow><annotation encoding="application/x-tex">P</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.1389em;">P</span></span></span></span> corresponds to <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>S</mi></mrow><annotation encoding="application/x-tex">S</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">S</span></span></span></span>. If the measure of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>Q</mi></mrow><annotation encoding="application/x-tex">Q</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8778em;vertical-align:-0.1944em;"></span><span class="mord mathnormal">Q</span></span></span></span> is <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup><mn>18</mn><mo>∘</mo></msup></mrow><annotation encoding="application/x-tex">18^\circ</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6741em;"></span><span class="mord">1</span><span class="mord"><span class="mord">8</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.6741em;"><span style="top:-3.063em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mbin mtight">∘</span></span></span></span></span></span></span></span></span></span></span>, what is the measure of angle <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>S</mi></mrow><annotation encoding="application/x-tex">S</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6833em;"></span><span class="mord mathnormal" style="margin-right:0.0576em;">S</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #67 · Full test · math · type: mcqBank-match candidate available
Currently stored (rendered) A group of students voted on five after-school activities. The bar graph shows the number of students who voted for each of the five activities. How many students chose activity 3?
(A) 25
(B) 39
(C) 48
(D) 50
Flag reason: update21 candidate match: confidence=MEDIUM; textSimilarity=0.73
Bank-match candidate (unverified)
The data for the 5 categories are as follows:
1: More than halfway above 25 students
2: Less than halfway above 30 students
3: More than halfway above 35 students
4: About halfway above 40 students
5: About halfway above 45 students
A group of students voted on five after-school activities. The bar graph shows the number of students who voted for each of the five activities. How many students chose activity 3 3 3 ?
Suggested correct answer: B
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d="M205.028,245.249a2.376,2.376,0,0,1,1.6.688,2.3,2.3,0,0,1,.766,1.793,2.439,2.439,0,0,1-.417,1.443,5.382,5.382,0,0,1-1.192,1.173,4.984,4.984,0,0,1,1.87,1.221,2.908,2.908,0,0,1,.844,2.132,3.732,3.732,0,0,1-1.3,2.965,4.744,4.744,0,0,1-3.217,1.124,4.545,4.545,0,0,1-2.519-.581.651.651,0,0,1-.194-.562q0-.912.717-.912a.582.582,0,0,1,.358.146,4.016,4.016,0,0,1,.407.378,3.428,3.428,0,0,0,.378.349,2.458,2.458,0,0,0,1.473.407,2.161,2.161,0,0,0,1.541-.669,2.878,2.878,0,0,0,.688-2.141,2.744,2.744,0,0,0-.737-1.938,2.28,2.28,0,0,0-1.724-.795,5.251,5.251,0,0,0-1.26.136.811.811,0,0,1-.136-.5.364.364,0,0,1,.039-.194,4.271,4.271,0,0,0,2.132-.93,2.4,2.4,0,0,0,.794-1.9,1.756,1.756,0,0,0-1.686-1.686,2.073,2.073,0,0,0-.785.145,2.048,2.048,0,0,0-.542.3,4.726,4.726,0,0,0-.359.339l-.193.2c-.052,0-.1-.061-.156-.184a.862.862,0,0,1-.077-.32,4.21,4.21,0,0,1,1.182-1.2A3.091,3.091,0,0,1,205.028,245.249Z" fill="#231f20"></path><path d="M263.821,245.191c.168,0,.252.065.252.194v7.81h1.2q.309,0,.31.93a.225.225,0,0,1-.116.194h-1.4v3.392q-.057.1-.813.1c-.479,0-.717-.052-.717-.155v-3.333h-4.9a1,1,0,0,1-.136-.6l5.872-8.295A.536.536,0,0,1,263.821,245.191Zm-1.278,8V248.04c0-.117-.033-.175-.1-.175a.056.056,0,0,1-.018.039l-3.528,5.058a.081.081,0,0,0-.019.059c0,.116.045.174.136.174Z" fill="#231f20"></path><path d="M316.182,245.617a41.3,41.3,0,0,0,4.554-.271.7.7,0,0,1,.1.407,5.435,5.435,0,0,1-.116,1.066,10.748,10.748,0,0,1-2.19.213l-1.686.077c-.065.014-.11.065-.136.156q-.213,1.065-.561,3.1a5.178,5.178,0,0,1,1.821-.252,3.789,3.789,0,0,1,2.684,1.066,3.349,3.349,0,0,1,1.134,2.52,3.82,3.82,0,0,1-1.25,2.936,4.471,4.471,0,0,1-3.149,1.153,4.716,4.716,0,0,1-2.6-.581.651.651,0,0,1-.194-.562q0-.912.717-.912a.587.587,0,0,1,.359.146,4.126,4.126,0,0,1,.406.378,3.428,3.428,0,0,0,.378.349,2.6,2.6,0,0,0,1.551.407,1.972,1.972,0,0,0,1.463-.688,3.006,3.006,0,0,0,.649-2.122,3.261,3.261,0,0,0-.136-.95,3.2,3.2,0,0,0-.435-.882,2.01,2.01,0,0,0-.882-.688,3.463,3.463,0,0,0-1.376-.252,5.666,5.666,0,0,0-1.686.214,1.429,1.429,0,0,1-.349-.272Z" fill="#231f20"></path></g></svg><div role="region" aria-label="Long description for bar graph" class="sr-only"><ul>
<li>The data for the 5 categories are as follows: <br />
<ul>
<li>1: More than halfway above 25 students</li>
<li>2: Less than halfway above 30 students</li>
<li>3: More than halfway above 35 students</li>
<li>4: About halfway above 40 students</li>
<li>5: About halfway above 45 students</li>
</ul>
</li>
</ul></div><p></p>
<p style="text-align: left;">A group of students voted on five after-school activities. The bar graph shows the number of students who voted for each of the five activities. How many students chose activity <span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>3</mn></mrow><annotation encoding="application/x-tex">3</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">3</span></span></span></span>?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #50 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Ancestral Puebloans, the civilization from which present-day Pueblo tribes descended, emerged as early as 1500 B.C.E. in an area of what is now the southwestern United States and dispersed suddenly in the late 1200s C.E., abandoning established villages with systems for farming crops and turkeys. Recent analysis comparing turkey remains at Mesa Verde, one such village in southern Colorado, to samples from modern turkey populations in the Rio Grande Valley of north central New Mexico determined that the latter birds descended in part from turkeys cultivated at Mesa Verde, with shared genetic markers appearing only after 1280. Thus, researchers concluded that _______ Which choice most logically completes the text?
(A) conditions of the terrains in the Rio Grande Valley and Mesa Verde had greater similarities in the past than they do today.
(B) some Ancestral Puebloans migrated to the Rio Grande Valley in the late 1200s and carried farming practices with them.
(C) Indigenous peoples living in the Rio Grande Valley primarily planted crops and did not cultivate turkeys before 1280.
(D) the Ancestral Puebloans of Mesa Verde likely adopted the farming practices of Indigenous peoples living in other regions.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Ancestral Puebloans, the civilization from which present-day Pueblo tribes descended, emerged as early as 1500 B.C.E. in an area of what is now the southwestern United States and dispersed suddenly in the late 1200s C.E., abandoning established villages with systems for farming crops and turkeys. Recent analysis comparing turkey remains at Mesa Verde, one such village in southern Colorado, to samples from modern turkey populations in the Rio Grande Valley of north central New Mexico determined that the latter birds descended in part from turkeys cultivated at Mesa Verde, with shared genetic markers appearing only after 1280. Thus, researchers concluded that ______ blank
Which choice most logically completes the text?
(A) conditions of the terrains in the Rio Grande Valley and Mesa Verde had greater similarities in the past than they do today.
(B) some Ancestral Puebloans migrated to the Rio Grande Valley in the late 1200s and carried farming practices with them.
(C) Indigenous peoples living in the Rio Grande Valley primarily planted crops and did not cultivate turkeys before 1280.
(D) the Ancestral Puebloans of Mesa Verde likely adopted the farming practices of Indigenous peoples living in other regions.
Suggested correct answer: B
Verified stem text <p>Ancestral Puebloans, the civilization from which present-day Pueblo tribes descended, emerged as early as 1500 B.C.E. in an area of what is now the southwestern United States and dispersed suddenly in the late 1200s C.E., abandoning established villages with systems for farming crops and turkeys. Recent analysis comparing turkey remains at Mesa Verde, one such village in southern Colorado, to samples from modern turkey populations in the Rio Grande Valley of north central New Mexico determined that the latter birds descended in part from turkeys cultivated at Mesa Verde, with shared genetic markers appearing only after 1280. Thus, researchers concluded that <span>______</span><span class="sr-only">blank</span></p>
<p>Which choice most logically completes the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #43 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Cats can judge unseen people’s positions in space by the sound of their voices and thus react with surprise when the same person calls to them from two different locations in a short span of time. Saho Takagi and colleagues reached this conclusion by measuring cats’ levels of surprise based on their ear and head movements while the cats heard recordings of their owners’ voices from two speakers spaced far apart. Cats exhibited a low level of surprise when owners’ voices were played twice from the same speaker, but they showed a high level of surprise when the voice was played once each from the two different speakers. According to the text, how did the researchers determine the level of surprise displayed by the cats in the study?
(A) They watched how each cat moved its ears and head.
(B) They examined how each cat reacted to the voice of a stranger.
(C) They studied how each cat physically interacted with its owner.
(D) They tracked how each cat moved around the room.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Cats can judge unseen people’s positions in space by the sound of their voices and thus react with surprise when the same person calls to them from two different locations in a short span of time. Saho Takagi and colleagues reached this conclusion by measuring cats’ levels of surprise based on their ear and head movements while the cats heard recordings of their owners’ voices from two speakers spaced far apart. Cats exhibited a low level of surprise when owners’ voices were played twice from the same speaker, but they showed a high level of surprise when the voice was played once each from the two different speakers.
According to the text, how did the researchers determine the level of surprise displayed by the cats in the study?
(A) They watched how each cat moved its ears and head.
(B) They examined how each cat reacted to the voice of a stranger.
(C) They studied how each cat physically interacted with its owner.
(D) They tracked how each cat moved around the room.
Suggested correct answer: A
Verified stem text <p>Cats can judge unseen people’s positions in space by the sound of their voices and thus react with surprise when the same person calls to them from two different locations in a short span of time. Saho Takagi and colleagues reached this conclusion by measuring cats’ levels of surprise based on their ear and head movements while the cats heard recordings of their owners’ voices from two speakers spaced far apart. Cats exhibited a low level of surprise when owners’ voices were played twice from the same speaker, but they showed a high level of surprise when the voice was played once each from the two different speakers.</p>
<p>According to the text, how did the researchers determine the level of surprise displayed by the cats in the study?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #39 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) For a 2020 exhibition, photographer and neurobiologist Okunola Jeyifous _______ a series of new images based on a series of alphabet posters from the 1970s known as the “Black ABCs,” which featured Black children from Chicago. Jeyifous photographed the now-adult models and layered the photos over magnified images of the models’ cells, resulting in what he called “micro and macro portraiture.” Which choice completes the text with the most logical and precise word or phrase?
(A) validated
(B) created
(C) challenged
(D) restored
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) For a 2020 exhibition, photographer and neurobiologist Okunola Jeyifous ______ blank a series of new images based on a series of alphabet posters from the 1970s known as the “Black ABCs,” which featured Black children from Chicago. Jeyifous photographed the now-adult models and layered the photos over magnified images of the models’ cells, resulting in what he called “micro and macro portraiture.”
Which choice completes the text with the most logical and precise word or phrase?
Suggested correct answer: B
Verified stem text <p>For a 2020 exhibition, photographer and neurobiologist Okunola Jeyifous <span>______</span><span class="sr-only">blank</span> a series of new images based on a series of alphabet posters from the 1970s known as the “Black ABCs,” which featured Black children from Chicago. Jeyifous photographed the now-adult models and layered the photos over magnified images of the models’ cells, resulting in what he called “micro and macro portraiture.”</p>
<p>Which choice completes the text with the most logical and precise word or phrase?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #31 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) While researching a topic, a student has taken the following notes: • Chemical leavening agents cause carbon dioxide to be released within a liquid batter, making the batter rise as it bakes. • Baking soda and baking powder are chemical leavening agents. • Baking soda is pure sodium bicarbonate. • To produce carbon dioxide, baking soda needs to be mixed with liquid and an acidic ingredient such as honey. • Baking powder is a mixture of sodium bicarbonate and an acid. • To produce carbon dioxide, baking powder needs to be mixed with liquid but not with an acidic ingredient. The student wants to emphasize a difference between baking soda and baking powder. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) To make batters rise, bakers use chemical leavening agents such as baking soda and baking powder.
(B) Baking soda and baking powder are chemical leavening agents that, when mixed with other ingredients, cause carbon dioxide to be released within a batter.
(C) Baking soda is pure sodium bicarbonate, and honey is a type of acidic ingredient.
(D) To produce carbon dioxide within a liquid batter, baking soda needs to be mixed with an acidic ingredient, whereas baking powder does not.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) While researching a topic, a student has taken the following notes:
Chemical leavening agents cause carbon dioxide to be released within a liquid batter, making the batter rise as it bakes.
Baking soda and baking powder are chemical leavening agents.
Baking soda is pure sodium bicarbonate.
To produce carbon dioxide, baking soda needs to be mixed with liquid and an acidic ingredient such as honey.
Baking powder is a mixture of sodium bicarbonate and an acid.
To produce carbon dioxide, baking powder needs to be mixed with liquid but not with an acidic ingredient.
The student wants to emphasize a difference between baking soda and baking powder. Which choice most effectively uses relevant information from the notes to accomplish this goal?
(A) To make batters rise, bakers use chemical leavening agents such as baking soda and baking powder.
(B) Baking soda and baking powder are chemical leavening agents that, when mixed with other ingredients, cause carbon dioxide to be released within a batter.
(C) Baking soda is pure sodium bicarbonate, and honey is a type of acidic ingredient.
(D) To produce carbon dioxide within a liquid batter, baking soda needs to be mixed with an acidic ingredient, whereas baking powder does not.
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p>While researching a topic, a student has taken the following notes:</p>
<ul>
<li>Chemical leavening agents cause carbon dioxide to be released within a liquid batter, making the batter rise as it bakes.</li>
<li>Baking soda and baking powder are chemical leavening agents.</li>
<li>Baking soda is pure sodium bicarbonate.</li>
<li>To produce carbon dioxide, baking soda needs to be mixed with liquid and an acidic ingredient such as honey.</li>
<li>Baking powder is a mixture of sodium bicarbonate and an acid.</li>
<li>To produce carbon dioxide, baking powder needs to be mixed with liquid but not with an acidic ingredient.</li>
</ul>
<p>The student wants to emphasize a difference between baking soda and baking powder. Which choice most effectively uses relevant information from the notes to accomplish this goal?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #29 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Samuel Coleridge-Taylor was a prominent classical music composer from England who toured the US three times in the early 1900s. The child of a West African father and an English mother, Coleridge- Taylor emphasized his mixed-race ancestry. For example, he referred to himself as Anglo-African. _______ he incorporated the sounds of traditional African music into his classical music compositions. Which choice completes the text with the most logical transition?
(A) In addition,
(B) Actually,
(C) However,
(D) Regardless,
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Samuel Coleridge-Taylor was a prominent classical music composer from England who toured the US three times in the early 1900s. The child of a West African father and an English mother, Coleridge-Taylor emphasized his mixed-race ancestry. For example, he referred to himself as Anglo-African. ______ blank he incorporated the sounds of traditional African music into his classical music compositions.
Which choice completes the text with the most logical transition?
Suggested correct answer: A
Verified stem text <p>Samuel Coleridge-Taylor was a prominent classical music composer from England who toured the US three times in the early 1900s. The child of a West African father and an English mother, Coleridge-Taylor emphasized his mixed-race ancestry. For example, he referred to himself as Anglo-African. <span>______</span><span class="sr-only">blank</span> he incorporated the sounds of traditional African music into his classical music compositions.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #28 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Geoscientists have long considered Hawaii’s Mauna Loa volcano to be Earth’s largest shield volcano by volume, measuring approximately 74,000 cubic kilometers. _______ according to a 2020 study by local geoscientist Michael Garcia, Hawaii’s Pūhāhonu shield volcano is significantly larger, boasting a volume of about 148,000 cubic kilometers. Which choice completes the text with the most logical transition?
(A) Secondly,
(B) Consequently,
(C) Moreover,
(D) However,
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Geoscientists have long considered Hawaii’s Mauna Loa volcano to be Earth’s largest shield volcano by volume, measuring approximately 74,000 cubic kilometers. ______ blank according to a 2020 study by local geoscientist Michael Garcia, Hawaii’s Pūhāhonu shield volcano is significantly larger, boasting a volume of about 148,000 cubic kilometers.
Which choice completes the text with the most logical transition?
Suggested correct answer: D mismatches stored answer "A" -- double check
Verified stem text <p>Geoscientists have long considered Hawaii’s Mauna Loa volcano to be Earth’s largest shield volcano by volume, measuring approximately 74,000 cubic kilometers. <span>______</span><span class="sr-only">blank</span> according to a 2020 study by local geoscientist Michael Garcia, Hawaii’s Pūhāhonu shield volcano is significantly larger, boasting a volume of about 148,000 cubic kilometers.</p>
<p>Which choice completes the text with the most logical transition?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #26 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) Sociologist Alton Okinaka sits on the review board tasked with adding new sites to the Hawai‘i Register of Historic Places, which includes Pi‘ilanihale Heiau and the ‘Ōpaeka‘a Road Bridge. Okinaka doesn’t make such decisions _______ all historical designations must be approved by a group of nine other experts from the fields of architecture, archaeology, history, and Hawaiian culture. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) single-handedly, however;
(B) single-handedly; however,
(C) single-handedly, however,
(D) single-handedly however
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Sociologist Alton Okinaka sits on the review board tasked with adding new sites to the Hawai‘i Register of Historic Places, which includes Pi‘ilanihale Heiau and the ‘Ōpaeka‘a Road Bridge. Okinaka doesn’t make such decisions ______ blank all historical designations must be approved by a group of nine other experts from the fields of architecture, archaeology, history, and Hawaiian culture.
Which choice completes the text so that it conforms to the conventions of Standard English?
(A) single-handedly, however;
(B) single-handedly; however,
(C) single-handedly, however,
Suggested correct answer: A
Verified stem text <p>Sociologist Alton Okinaka sits on the review board tasked with adding new sites to the Hawai‘i Register of Historic Places, which includes Pi‘ilanihale Heiau and the ‘Ōpaeka‘a Road Bridge. Okinaka doesn’t make such decisions <span>______</span><span class="sr-only">blank</span> all historical designations must be approved by a group of nine other experts from the fields of architecture, archaeology, history, and Hawaiian culture.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #23 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) Seneca sculptor Marie Watt’s blanket art comes in a range of shapes and sizes. In 2004, Watt sewed strips of blankets together to craft a 10-by-13-inch _______ in 2014, she arranged folded blankets into two large stacks and then cast them in bronze, creating two curving 18-foot-tall blue-bronze pillars. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) sampler later,
(B) sampler;
(C) sampler,
(D) sampler, later,
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) Seneca sculptor Marie Watt’s blanket art comes in a range of shapes and sizes. In 2004, Watt sewed strips of blankets together to craft a 10-by-13-inch ______ blank in 2014, she arranged folded blankets into two large stacks and then cast them in bronze, creating two curving 18-foot-tall blue-bronze pillars.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: B mismatches stored answer "D" -- double check
Verified stem text <p>Seneca sculptor Marie Watt’s blanket art comes in a range of shapes and sizes. In 2004, Watt sewed strips of blankets together to craft a 10-by-13-inch <span>______</span><span class="sr-only">blank</span> in 2014, she arranged folded blankets into two large stacks and then cast them in bronze, creating two curving 18-foot-tall blue-bronze pillars.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #22 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) In many of her landscape paintings from the 1970s and 1980s, Lebanese American artist Etel Adnan worked to capture the essence of California’s fog-shrouded Mount Tamalpais region through abstraction, using splotches of color to represent the area’s features. Interestingly, the triangle representing the mountain itself _______ among the few defined figures in her paintings. Which choice completes the text so that it conforms to the conventions of Standard English?
(A) are
(B) have been
(C) were
(D) is
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=0.99; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) In many of her landscape paintings from the 1970s and 1980s, Lebanese American artist Etel Adnan worked to capture the essence of California’s fog-shrouded Mount Tamalpais region through abstraction, using splotches of color to represent the area’s features. Interestingly, the triangle representing the mountain itself ______ blank among the few defined figures in her paintings.
Which choice completes the text so that it conforms to the conventions of Standard English?
Suggested correct answer: D
Verified stem text <p>In many of her landscape paintings from the 1970s and 1980s, Lebanese American artist Etel Adnan worked to capture the essence of California’s fog-shrouded Mount Tamalpais region through abstraction, using splotches of color to represent the area’s features. Interestingly, the triangle representing the mountain itself <span>______</span><span class="sr-only">blank</span> among the few defined figures in her paintings.</p>
<p>Which choice completes the text so that it conforms to the conventions of Standard English?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #11 · Full test · rw · type: mcqBank-match candidate available
Currently stored (rendered) The following text is from Ezra Pound’s 1909 poem
“Hymn III,” based on the work of Marcantonio
Flaminio.
As a fragile and lovely flower unfolds its gleaming
foliage on the breast of the fostering earth, if
the dew and the rain draw it forth;
So doth my tender mind flourish, if it be fed with the
sweet dew of the fostering spirit,
Lacking this, it beginneth straightway to languish,
even as a floweret born upon dry earth, if the
dew and the rain tend it not.
Based on the text, in what way is the human mind
like a flower?
(A) It becomes increasingly vigorous with the passage of time.
(B) It draws strength from changes in the weather.
(C) It requires proper nourishment in order to thrive.
(D) It perseveres despite challenging circumstances.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The following text is from Ezra Pound’s 1909 poem “Hymn III,” based on the work of Marcantonio Flaminio.
As a fragile and lovely flower unfolds its gleaming foliage on the breast of the fostering earth, if the dew and the rain draw it forth; So doth my tender mind flourish, if it be fed with the sweet dew of the fostering spirit, Lacking this, it beginneth straightway to languish, even as a floweret born upon dry earth, if the dew and the rain tend it not.
Based on the text, in what way is the human mind like a flower?
(A) It becomes increasingly vigorous with the passage of time.
(B) It draws strength from changes in the weather.
(C) It requires proper nourishment in order to thrive.
(D) It perseveres despite challenging circumstances.
Suggested correct answer: C mismatches stored answer "D" -- double check
Verified stem text <p>The following text is from Ezra Pound’s 1909 poem “Hymn III,” based on the work of Marcantonio Flaminio.</p>
<p style="padding-left:1em;">As a fragile and lovely flower unfolds its gleaming<br /> foliage on the breast of the fostering earth, if<br /> the dew and the rain draw it forth;<br />So doth my tender mind flourish, if it be fed with the<br /> sweet dew of the fostering spirit,<br />Lacking this, it beginneth straightway to languish,<br /> even as a floweret born upon dry earth, if the<br /> dew and the rain tend it not.</p>
<p>Based on the text, in what way is the human mind like a flower?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #10 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The following text is adapted from Frances Hodgson Burnett’s 1911 novel The Secret Garden. Mary, a young girl, recently found an overgrown hidden garden. Mary was an odd, determined little person, and now she had something interesting to be determined about, she was very much absorbed, indeed. She worked and dug and pulled up weeds steadily, only becoming more pleased with her work every hour instead of tiring of it. It seemed to her like a fascinating sort of play. Which choice best states the main idea of the text?
(A) Mary hides in the garden to avoid doing her chores.
(B) Mary is getting bored with pulling up so many weeds in the garden.
(C) Mary is clearing out the garden to create a space to play.
(D) Mary feels very satisfied when she’s taking care of the garden.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The following text is adapted from Frances Hodgson Burnett’s 1911 novel The Secret Garden . Mary, a young girl, recently found an overgrown hidden garden.
Mary was an odd, determined little person, and now she had something interesting to be determined about, she was very much absorbed, indeed. She worked and dug and pulled up weeds steadily, only becoming more pleased with her work every hour instead of tiring of it. It seemed to her like a fascinating sort of play.
Which choice best states the main idea of the text?
(A) Mary hides in the garden to avoid doing her chores.
(B) Mary is getting bored with pulling up so many weeds in the garden.
(C) Mary is clearing out the garden to create a space to play.
(D) Mary feels very satisfied when she’s taking care of the garden.
Suggested correct answer: D
Verified stem text <p>The following text is adapted from Frances Hodgson Burnett’s 1911 novel <em>The Secret Garden</em>. Mary, a young girl, recently found an overgrown hidden garden.</p>
<p style="padding-left: 1em;">Mary was an odd, determined little person, and now she had something interesting to be determined about, she was very much absorbed, indeed. She worked and dug and pulled up weeds steadily, only becoming more pleased with her work every hour instead of tiring of it. It seemed to her like a fascinating sort of play.</p>
<p>Which choice best states the main idea of the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference) Question #8 · Full test · rw · type: mcqno answer key Bank-match candidate available
Currently stored (rendered) The mimosa tree evolved in East Asia, where the beetle Bruchidius terrenus preys on its seeds. In 1785, mimosa trees were introduced to North America, far from any B. terrenus. But evolutionary links between predators and their prey can persist across centuries and continents. Around 2001, B. terrenus was introduced in southeastern North America near where botanist Shu-Mei Chang and colleagues had been monitoring mimosa trees. Within a year, 93 percent of the trees had been attacked by the beetles. Which choice best describes the function of the third sentence in the overall structure of the text?
(A) It states the hypothesis that Chang and colleagues had set out to investigate using mimosa trees and B. terrenus.
(B) It presents a generalization that is exemplified by the discussion of the mimosa trees and B. terrenus.
(C) It offers an alternative explanation for the findings of Chang and colleagues.
(D) It provides context that clarifies why the species mentioned spread to new locations.
Flag reason: update21 candidate match: confidence=HIGH; textSimilarity=1.00; answer-key DISAGREES with candidate -- needs human confirmation
Bank-match candidate (unverified) The mimosa tree evolved in East Asia, where the beetle Bruchidius terrenus preys on its seeds. In 1785, mimosa trees were introduced to North America, far from any B. terrenus . But evolutionary links between predators and their prey can persist across centuries and continents. Around 2001, B. terrenus was introduced in southeastern North America near where botanist Shu-Mei Chang and colleagues had been monitoring mimosa trees. Within a year, 93 percent of the trees had been attacked by the beetles.
Which choice best describes the function of the third sentence in the overall structure of the text?
(A) It states the hypothesis that Chang and colleagues had set out to investigate using mimosa trees and B. terrenus .
(B) It presents a generalization that is exemplified by the discussion of the mimosa trees and B. terrenus .
(C) It provides context that clarifies why the species mentioned spread to new locations.
(D) It offers an alternative explanation for the findings of Chang and colleagues.
Suggested correct answer: B
Verified stem text <p>The mimosa tree evolved in East Asia, where the beetle <em>Bruchidius terrenus</em> preys on its seeds. In 1785, mimosa trees were introduced to North America, far from any <em>B. terrenus</em>. <u>But evolutionary links between predators and their prey can persist across centuries and continents.</u> Around 2001, <em>B. terrenus</em> was introduced in southeastern North America near where botanist Shu-Mei Chang and colleagues had been monitoring mimosa trees. Within a year, 93 percent of the trees had been attacked by the beetles. </p>
<p>Which choice best describes the function of the third sentence in the overall structure of the text?</p> Choices (leave blank for a grid-in question) A
B
C
D
Correct answer (letter A-D, or the grid-in value) Accept suggestion & unflag Source PDF page (reference)