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<h2>SL Paper 3</h2><div class="specification">
<p>A radio wave of wavelength <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span> is incident on a conductor. The graph shows the variation with&nbsp;wavelength <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span> of the maximum distance <em>d</em> travelled inside the conductor.</p>
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"></p>
</div>

<div class="specification">
<p>For <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span> = 5.0 x&nbsp;10<sup>5</sup> m, calculate the</p>
</div>

<div class="specification">
<p>The graph shows the variation with wavelength <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span> of <em>d </em><sup>2</sup>. Error bars are not shown and&nbsp;the line of best-fit has been drawn.</p>
<p style="text-align: center;"><img 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"></p>
<p>A student states that the equation of the line of best-fit is <em>d </em><sup>2</sup><sup>&nbsp;</sup>= <em>a</em> + <em>b</em><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span>. When <em>d </em><sup>2</sup>&nbsp;and <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ<!-- λ --></mi>
</math></span> are expressed in terms of fundamental SI units, the student finds that <em>a</em> = 0.040 x&nbsp;10<sup>–4</sup>&nbsp;and <em>b</em> = 1.8 x&nbsp;10<sup>–11</sup>.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Suggest why it is unlikely that the relation between<em> d</em> and <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ</mi>
</math></span> is linear.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>fractional uncertainty in <em>d</em>.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>percentage uncertainty in <em>d </em><sup>2</sup>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State the fundamental SI unit of the constant <em>a</em> and of the constant <em>b</em>.</p>
<p><img src="data:image/png;base64,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"></p>
<div class="marks">[2]</div>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Determine the distance travelled inside the conductor by very high frequency&nbsp;electromagnetic waves.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.ii.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>it is not possible to draw a straight line through all the&nbsp;error bars<br><em><strong>OR</strong></em><br>the line of best-fit is curved/not a straight line</p>
<p>&nbsp;</p>
<p><em>Treat as neutral any reference to the origin.</em></p>
<p><em>Allow “linear” for “straight line”.</em></p>
<p><strong><em>[1 mark]</em></strong></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><em>d</em>&nbsp;= 0.35 ± 0.01 <em><strong>AND</strong></em> Δ<em>d</em>&nbsp;= 0.05 ± 0.01 «cm»</p>
<p>«<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{\Delta d}}{d} = \frac{{0.5}}{{0.35}}">
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>d</mi>
    </mrow>
    <mi>d</mi>
  </mfrac>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>0.5</mn>
    </mrow>
    <mrow>
      <mn>0.35</mn>
    </mrow>
  </mfrac>
</math></span>» = 0.14</p>
<p><em><strong>OR</strong></em></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{7}">
  <mfrac>
    <mn>1</mn>
    <mn>7</mn>
  </mfrac>
</math></span>&nbsp;<em><strong>or</strong></em> 14% <em><strong>or</strong></em> 0.1</p>
<p>&nbsp;</p>
<p><em>Allow final answers in the range of 0.11 to 0.18.</em></p>
<p><em>Allow <strong>[1 max]</strong> for 0.03 to 0.04 if <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda ">
  <mi>λ</mi>
</math></span> = 5 × 10<sup>6</sup> m is used.</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>28 to 30%</p>
<p>&nbsp;</p>
<p><em>Allow ECF from (b)(i), but only accept answer as a %</em></p>
<p><strong><em>[1 mark]</em></strong></p>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><em>a:</em> m<sup>2</sup></p>
<p><em>b:</em> m</p>
<p>&nbsp;</p>
<p><em>Allow answers in words</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><em><strong>ALTERNATIVE 1</strong> </em>– if graph on page 4 is used</p>
<p><em>d </em><sup>2</sup> =&nbsp;0.040 x 10<sup>–4</sup> «m<sup>2</sup>»</p>
<p><em>d</em> =&nbsp;0.20&nbsp;x 10<sup>–2</sup> «m»</p>
<p><em><strong>ALTERNATIVE 2</strong></em> – if graph on page 2 is used</p>
<p>any evidence that <em>d</em> intercept has been determined</p>
<p><em>d</em>&nbsp;= 0.20 ± 0.05 «cm»</p>
<p>&nbsp;</p>
<p>&nbsp;</p>
<p><em>For MP1 accept answers in range of 0.020 to 0.060 «cm<sup>2</sup>» if&nbsp;they fail to use given value of “a”.</em></p>
<p><em>For MP2 accept answers in range 0.14 to 0.25 «cm» .</em></p>
<p><em><strong>[2 marks]</strong></em></p>
<div class="question_part_label">c.ii.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.ii.</div>
</div>
<br><hr><br><div class="specification">
<p>The equipment shown in the diagram was used by a student to investigate the variation with&nbsp;volume, of the pressure <em>p</em> of air, at constant temperature. The air was trapped in a tube of&nbsp;constant cross-sectional area above a column of oil.</p>
<p style="text-align: center;"><img src="data:image/png;base64,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"></p>
<p>The pump forces oil to move up the tube decreasing the volume of the trapped air.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The student measured the height <em>H</em> of the air column and the corresponding air&nbsp;pressure <em>p</em>. After each reduction in the volume the student waited for some time before&nbsp;measuring the pressure. Outline why this was necessary.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The following graph of <em>p</em> versus <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{H}">
  <mfrac>
    <mn>1</mn>
    <mi>H</mi>
  </mfrac>
</math></span> was obtained. Error bars were negligibly small.</p>
<p><img 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"></p>
<p>The equation of the line of best fit is <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="p = a + \frac{b}{H}">
  <mi>p</mi>
  <mo>=</mo>
  <mi>a</mi>
  <mo>+</mo>
  <mfrac>
    <mi>b</mi>
    <mi>H</mi>
  </mfrac>
</math></span>.</p>
<p>Determine the value of <em>b</em> including an appropriate unit.</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Outline how the results of this experiment are consistent with the ideal gas law at constant temperature.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The cross-sectional area of the tube is 1.3 × 10<sup>–3</sup><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\,">
  <mspace width="thinmathspace"></mspace>
</math></span>m<sup>2</sup> and the temperature of air is 300 K. Estimate the number of moles of air in the tube.</p>
<div class="marks">[2]</div>
<div class="question_part_label">d.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The equation in (b) may be used to predict the pressure of the air at extremely large values of <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{H}">
  <mfrac>
    <mn>1</mn>
    <mi>H</mi>
  </mfrac>
</math></span>. Suggest why this will be an unreliable estimate of the pressure.</p>
<div class="marks">[2]</div>
<div class="question_part_label">e.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>in order to keep the temperature constant</p>
<p>in order to allow the system to reach thermal equilibrium with the surroundings/OWTTE</p>
<p>&nbsp;</p>
<p>Accept answers in terms of pressure or volume changes only if clearly related to reaching thermal equilibrium with the surroundings.</p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>recognizes <em>b</em> as gradient</p>
<p>calculates <em>b</em> in range 4.7 × 10<sup>4</sup> to 5.3 × 10<sup>4</sup></p>
<p>Pa<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\,">
  <mspace width="thinmathspace"></mspace>
</math></span>m</p>
<p>&nbsp;</p>
<p><em>Award <strong>[2 max]</strong> if POT error in b.</em><br><em>Allow any correct SI unit, eg kg<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\,">
  <mspace width="thinmathspace"></mspace>
</math></span>s<sup>–2</sup>.</em></p>
<p><strong><em>[3 marks]</em></strong></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="V \propto H">
  <mi>V</mi>
  <mo>∝</mo>
  <mi>H</mi>
</math></span> thus ideal gas law gives <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="p \propto \frac{1}{H}">
  <mi>p</mi>
  <mo>∝</mo>
  <mfrac>
    <mn>1</mn>
    <mi>H</mi>
  </mfrac>
</math></span></p>
<p><strong>so</strong> graph<strong> should be</strong> «a straight line through origin,» as<strong> observed</strong></p>
<p><em><strong>[2 marks]</strong></em></p>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="n = \frac{{bA}}{{RT}}">
  <mi>n</mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mi>b</mi>
      <mi>A</mi>
    </mrow>
    <mrow>
      <mi>R</mi>
      <mi>T</mi>
    </mrow>
  </mfrac>
</math></span>&nbsp;<em><strong>OR </strong></em>correct substitution of one point from the graph</p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="n = \frac{{5 \times {{10}^4} \times 1.3 \times {{10}^{ - 3}}}}{{8.31 \times 300}} = 0.026 \approx 0.03">
  <mi>n</mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>5</mn>
      <mo>×</mo>
      <mrow>
        <msup>
          <mrow>
            <mn>10</mn>
          </mrow>
          <mn>4</mn>
        </msup>
      </mrow>
      <mo>×</mo>
      <mn>1.3</mn>
      <mo>×</mo>
      <mrow>
        <msup>
          <mrow>
            <mn>10</mn>
          </mrow>
          <mrow>
            <mo>−</mo>
            <mn>3</mn>
          </mrow>
        </msup>
      </mrow>
    </mrow>
    <mrow>
      <mn>8.31</mn>
      <mo>×</mo>
      <mn>300</mn>
    </mrow>
  </mfrac>
  <mo>=</mo>
  <mn>0.026</mn>
  <mo>≈</mo>
  <mn>0.03</mn>
</math></span></p>
<p>&nbsp;</p>
<p><em>Answer must be to 1 or 2 SF. </em></p>
<p><em>Allow ECF from (b).</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">d.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>very large <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{H}">
  <mfrac>
    <mn>1</mn>
    <mi>H</mi>
  </mfrac>
</math></span> means very small volumes / very high pressures</p>
<p>at very small volumes the ideal gas does not apply<br><em><strong>OR</strong></em><br>at very small volumes some of the assumptions of the kinetic theory of gases do not hold</p>
<p><em><strong>[2 marks]</strong></em></p>
<div class="question_part_label">e.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">d.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">e.</div>
</div>
<br><hr><br><div class="specification">
<p>An apparatus is used to verify a gas law. The glass jar contains a fixed volume of air. Measurements can be taken using the thermometer and the pressure gauge.</p>
<p style="text-align: center;"><img src="data:image/png;base64,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"></p>
<p>The apparatus is cooled in a freezer and then placed in a water bath so that the temperature of the gas increases slowly. The pressure and temperature of the gas are recorded.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The graph shows the data recorded.</p>
<p><img src="data:image/png;base64,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"></p>
<p>Identify the fundamental SI unit for the gradient of the pressure–temperature graph.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The experiment is repeated using a different gas in the glass jar. The pressure for both experiments is low and both gases can be considered to be ideal.</p>
<p>(i) Using the axes provided in (a), draw the expected graph for this second experiment.</p>
<p>(ii) Explain the shape and intercept of the graph you drew in (b)(i).</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>kg m<sup>–1 </sup>s<sup>–2 </sup>K<sup>–1</sup></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>i</p>
<p>any straight line that either goes or would go, if extended, through the origin</p>
<p> </p>
<p>ii</p>
<p>for ideal gas <em>p</em> is proportional to <em>T</em> / P= nRT/V</p>
<p>gradient is constant /graph is a straight line</p>
<p>line passes through origin / 0,0 </p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>In a simple pendulum experiment, a student measures the period <em>T</em> of the pendulum many times and obtains an average value <em>T</em> = (2.540 ± 0.005) s. The length <em>L</em> of the pendulum is measured to be <em>L</em> = (1.60 ± 0.01) m.</p>
<p>Calculate, using <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="g = \frac{{4{\pi ^2}L}}{{{T^2}}}">
  <mi>g</mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>4</mn>
      <mrow>
        <msup>
          <mi>π</mi>
          <mn>2</mn>
        </msup>
      </mrow>
      <mi>L</mi>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mi>T</mi>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span>, the value of the acceleration of free fall, including its&nbsp;uncertainty. State the value of the uncertainty to one significant figure.</p>
<div class="marks">[3]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>In a different experiment a student investigates the dependence of the period <em>T</em> of a simple pendulum on the amplitude of oscillations <em>θ</em>. The graph shows the variation of <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{T}{{{T_0}}}">
  <mfrac>
    <mi>T</mi>
    <mrow>
      <mrow>
        <msub>
          <mi>T</mi>
          <mn>0</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
</math></span> with <em>θ</em>, where <em>T</em><sub>0</sub> is the period for small amplitude oscillations.</p>
<p><img 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"></p>
<p>The period may be considered to be independent of the amplitude <em>θ</em> as long as <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{T - {T_0}}}{{{T_0}}} < 0.01">
  <mfrac>
    <mrow>
      <mi>T</mi>
      <mo>−</mo>
      <mrow>
        <msub>
          <mi>T</mi>
          <mn>0</mn>
        </msub>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <msub>
          <mi>T</mi>
          <mn>0</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
  <mo>&lt;</mo>
  <mn>0.01</mn>
</math></span>. Determine the maximum value of <em>θ</em> for which the period is independent&nbsp;of the amplitude.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="g = \frac{{4{\pi ^2} \times 1.60}}{{{{2.540}^2}}} = 9.7907">
  <mi>g</mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>4</mn>
      <mrow>
        <msup>
          <mi>π</mi>
          <mn>2</mn>
        </msup>
      </mrow>
      <mo>×</mo>
      <mn>1.60</mn>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mrow>
            <mn>2.540</mn>
          </mrow>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
  <mo>=</mo>
  <mn>9.7907</mn>
</math></span></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\Delta g = g\left( {\frac{{\Delta L}}{L} + 2 \times \frac{{\Delta T}}{T}} \right) = ">
  <mi mathvariant="normal">Δ</mi>
  <mi>g</mi>
  <mo>=</mo>
  <mi>g</mi>
  <mrow>
    <mo>(</mo>
    <mrow>
      <mfrac>
        <mrow>
          <mi mathvariant="normal">Δ</mi>
          <mi>L</mi>
        </mrow>
        <mi>L</mi>
      </mfrac>
      <mo>+</mo>
      <mn>2</mn>
      <mo>×</mo>
      <mfrac>
        <mrow>
          <mi mathvariant="normal">Δ</mi>
          <mi>T</mi>
        </mrow>
        <mi>T</mi>
      </mfrac>
    </mrow>
    <mo>)</mo>
  </mrow>
  <mo>=</mo>
</math></span>&nbsp;«<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="9.7907\left( {\frac{{0.01}}{{1.60}} + 2 \times \frac{{0.005}}{{2.540}}} \right) = ">
  <mn>9.7907</mn>
  <mrow>
    <mo>(</mo>
    <mrow>
      <mfrac>
        <mrow>
          <mn>0.01</mn>
        </mrow>
        <mrow>
          <mn>1.60</mn>
        </mrow>
      </mfrac>
      <mo>+</mo>
      <mn>2</mn>
      <mo>×</mo>
      <mfrac>
        <mrow>
          <mn>0.005</mn>
        </mrow>
        <mrow>
          <mn>2.540</mn>
        </mrow>
      </mfrac>
    </mrow>
    <mo>)</mo>
  </mrow>
  <mo>=</mo>
</math></span>» 0.0997</p>
<p><em><strong>OR</strong></em></p>
<p>1.0%</p>
<p>hence g = (9.8 ± 0.1) «m<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\,">
  <mspace width="thinmathspace"></mspace>
</math></span>s<sup>−2</sup>» <em><strong>OR</strong></em>&nbsp;Δ<em>g&nbsp;</em>= 0.1 «m<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\,">
  <mspace width="thinmathspace"></mspace>
</math></span>s<sup>−2</sup>»</p>
<p>&nbsp;</p>
<p><em>For the first marking point answer must be given to at least 2 dp.</em><br><em>Accept calculations based on</em></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{g_{\max }} = 9.8908">
  <mrow>
    <msub>
      <mi>g</mi>
      <mrow>
        <mo movablelimits="true" form="prefix">max</mo>
      </mrow>
    </msub>
  </mrow>
  <mo>=</mo>
  <mn>9.8908</mn>
</math></span></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{g_{\min }} = 9.6913">
  <mrow>
    <msub>
      <mi>g</mi>
      <mrow>
        <mo movablelimits="true" form="prefix">min</mo>
      </mrow>
    </msub>
  </mrow>
  <mo>=</mo>
  <mn>9.6913</mn>
</math></span></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{{g_{\max }} - {g_{\min }}}}{2} = 0.099 \approx 0.1">
  <mfrac>
    <mrow>
      <mrow>
        <msub>
          <mi>g</mi>
          <mrow>
            <mo movablelimits="true" form="prefix">max</mo>
          </mrow>
        </msub>
      </mrow>
      <mo>−</mo>
      <mrow>
        <msub>
          <mi>g</mi>
          <mrow>
            <mo movablelimits="true" form="prefix">min</mo>
          </mrow>
        </msub>
      </mrow>
    </mrow>
    <mn>2</mn>
  </mfrac>
  <mo>=</mo>
  <mn>0.099</mn>
  <mo>≈</mo>
  <mn>0.1</mn>
</math></span></p>
<p><strong><em>[3 marks]</em></strong></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{T}{{{T_0}}} = 1.01">
  <mfrac>
    <mi>T</mi>
    <mrow>
      <mrow>
        <msub>
          <mi>T</mi>
          <mn>0</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
  <mo>=</mo>
  <mn>1.01</mn>
</math></span></p>
<p><em>θ</em><sub>max&nbsp;</sub>= 22&nbsp;«º»</p>
<p>&nbsp;</p>
<p><em>Accept answer from interval 20 to 24.</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="specification">
<p>The circuit shown may be used to measure the internal resistance of a cell.</p>
<p style="text-align: center;"><img src="images/Schermafbeelding_2017-09-27_om_07.51.02.png" alt="M17/4/PHYSI/SP3/ENG/TZ2/02"></p>
</div>

<div class="specification">
<p>The ammeter used in the experiment in (b) is an analogue meter. The student takes&nbsp;measurements without checking for a “zero error” on the ammeter.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>An ammeter and a voltmeter are connected in the circuit. Label the ammeter with the&nbsp;letter A and the voltmeter with the letter V.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>In one experiment a student obtains the following graph showing the variation with&nbsp;current <em>I</em> of the potential difference <em>V</em> across the cell.</p>
<p><img src="images/Schermafbeelding_2017-09-27_om_08.05.10.png" alt="M17/4/PHYSI/SP3/ENG/TZ2/02b"></p>
<p>Using the graph, determine the best estimate of the internal resistance of the cell.</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State what is meant by a zero error.</p>
<div class="marks">[1]</div>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>After taking measurements the student observes that the ammeter has a&nbsp;positive zero error. Explain what effect, if any, this zero error will have on the&nbsp;calculated value of the internal resistance in (b).</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.ii.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>correct labelling of both instruments</p>
<p>&nbsp;</p>
<p><img src="data:image/png;base64,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"></p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><em>V =&nbsp;E – Ir</em></p>
<p>large triangle to find gradient and correct read-offs&nbsp;from the line<br><em><strong>OR</strong></em><br>use of intercept <em>E</em> =&nbsp;1.5 V and another correct data&nbsp;point</p>
<p>internal resistance =&nbsp;0.60 Ω</p>
<p><em>For MP1 – do not award if only <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="R = \frac{V}{I}">
  <mi>R</mi>
  <mo>=</mo>
  <mfrac>
    <mi>V</mi>
    <mi>I</mi>
  </mfrac>
</math></span> is used.</em></p>
<p><em>For MP2 points at least 1A apart must be used.</em></p>
<p><em>For MP3 accept final answers in the range of 0.55 Ω to 0.65 Ω.</em></p>
<p><strong><em>[3 marks]</em></strong></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>a non-zero reading when a zero reading is expected/no current is&nbsp;flowing<br><em><strong>OR</strong></em><br>a calibration error</p>
<p>&nbsp;</p>
<p><em>OWTTE</em><br><em>Do not accept just “systematic error”.</em></p>
<p><strong><em>[1 mark]</em></strong></p>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>the error causes «all» measurements to be high/different/incorrect</p>
<p>effect on calculations/gradient will cancel out<br><em><strong>OR</strong></em><br>effect is that value for <em>r</em> is unchanged</p>
<p><em>Award <strong>[1 max]</strong> for statement of “no effect” without&nbsp;valid argument.</em></p>
<p><em>OWTTE</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">c.ii.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.ii.</div>
</div>
<br><hr><br><div class="specification">
<p>A student studies the relationship between the centripetal force applied to an object undergoing circular motion and its period <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math>.</p>
<p>The object (mass <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi></math>) is attached by a light inextensible string, through a tube, to a weight <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math> which hangs vertically. The string is free to move through the tube. A student swings the mass in a horizontal, circular path, adjusting the period <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math>&nbsp;of the motion until the radius <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>r</mi></math> is constant. The radius of the circle and the mass of the object are measured and remain constant for the entire experiment.</p>
<p><img style="display: block; margin-left: auto; margin-right: auto;" src="data:image/png;base64,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"></p>
<p style="text-align: center;">© International Baccalaureate Organization 2020.</p>
<p>The student collects the measurements of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> five times, for weight <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math>. The weight is then doubled (<math xmlns="http://www.w3.org/1998/Math/MathML"><mn>2</mn><mi>W</mi></math>) and the data collection repeated. Then it is repeated with <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>3</mn><mi>W</mi></math> and <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>4</mn><mi>W</mi></math>. The results are expected to support the relationship</p>
<p style="text-align: center;"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi><mo>=</mo><mfrac><mrow><mn>4</mn><msup><mi mathvariant="normal">π</mi><mn>2</mn></msup><mi>m</mi><mi>r</mi></mrow><msup><mi>T</mi><mn>2</mn></msup></mfrac><mo>.</mo></math></p>
</div>

<div class="specification">
<p>In reality, there is friction in the system, so in this case <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math> is less than the total centripetal force in the system. A suitable graph is plotted to determine the value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> experimentally. The value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> was also calculated directly from the measured values of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi></math> and <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>r</mi></math>.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State why the experiment is repeated with different values of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Predict from the equation whether the value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> found experimentally will be larger, the same or smaller than the value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> calculated directly.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The measurements of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> were collected five times. Explain how repeated measurements of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> reduced the random error in the final experimental value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math>.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c(i).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Outline why repeated measurements of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> would not reduce any systematic error in <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">c(ii).</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">In order to draw a graph « of </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math> </span><span class="fontstyle0">versus <math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mn>1</mn><msup><mi mathvariant="normal">T</mi><mn>2</mn></msup></mfrac></math> »<br></span><span class="fontstyle3"><em><strong>OR</strong></em><br></span></p>
<p><span class="fontstyle0">to confirm proportionality between «<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math></span><span class="fontstyle2"> </span><span class="fontstyle0">and </span><math xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi>T</mi><mrow><mo>-</mo><mn>2</mn></mrow></msup></math> <span class="fontstyle2">»<br></span></p>
<p><span class="fontstyle3"><em><strong>OR</strong></em><br></span></p>
<p><span class="fontstyle0">to confirm relationship between «<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math></span><span class="fontstyle2"> </span><span class="fontstyle0">and </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> »<br></span></p>
<p><em><span class="fontstyle3"><strong>OR</strong></span></em><span class="fontstyle3"><br></span></p>
<p><span class="fontstyle0">because </span><span class="fontstyle2">W </span><span class="fontstyle0">is the independent variable in the experiment </span><span class="fontstyle4">✓</span></p>
<p> </p>
<p><em><span class="fontstyle2">OWTTE</span></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0"><strong>ALTERNATIVE 1</strong></span></p>
<p><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi><mo>+</mo><mpadded lspace="-1px"><mi>friction</mi></mpadded><mo>=</mo><mfrac><mrow><mn>4</mn><msup><mi mathvariant="normal">π</mi><mn>2</mn></msup><mi>m</mi><mi>r</mi></mrow><msup><mi>T</mi><mn>2</mn></msup></mfrac></math></span></p>
<p><span class="fontstyle3"><em><strong>OR</strong></em></span></p>
<p><span class="fontstyle2">centripetal force is larger «than <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math>» / <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>W</mi></math> is smaller «than centripetal» </span><span class="fontstyle4">✓</span></p>
<p><span class="fontstyle2">«so» experimental </span><span class="fontstyle5"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> </span><span class="fontstyle2">is smaller «than calculated value» </span><span class="fontstyle4">✓</span></p>
<p> </p>
<p><strong><span class="fontstyle0">ALTERNATIVE 2 </span></strong><span class="fontstyle2"><strong>(refers to graph)</strong><br></span></p>
<p><span class="fontstyle2">reference to «friction force is» a systematic error «and does not affect gradient» </span><span class="fontstyle4">✓</span></p>
<p><span class="fontstyle2">«so» </span><span class="fontstyle5"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>m</mi><mi>r</mi></math> </span><span class="fontstyle2">is the same </span><span class="fontstyle4">✓</span></p>
<p> </p>
<p><em><span class="fontstyle5">MP2 awarded only with correct justification.<br>Candidates can gain zero, MP1 alone or full marks.</span></em></p>
<p><em><span class="fontstyle5">OWTTE</span></em></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">mention of mean/average value «of </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math></span><span class="fontstyle0">» </span><span class="fontstyle3">✓</span></p>
<p><span class="fontstyle0">this reduces uncertainty in </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>T</mi></math> </span><span class="fontstyle0">/ result<br></span><span class="fontstyle4"><em><strong>OR</strong></em><br></span><span class="fontstyle0">more accurate/precise </span><span class="fontstyle3">✓</span></p>
<p> </p>
<p><em><span class="fontstyle2">Reference to “random errors average out” scores MP1</span></em></p>
<p><em><span class="fontstyle2">Accept “closer to true value”, “more reliable value” OWTTE for MP2</span></em></p>
<p> </p>
<div class="question_part_label">c(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">systematic errors «usually» constant/always present/ not influenced by repetition </span><span class="fontstyle2">✓</span></p>
<p> </p>
<p><em><span class="fontstyle3">OWTTE</span></em></p>
<div class="question_part_label">c(ii).</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Most candidates scored. Different wording was used to express the aim of confirming the relationship.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Most successful candidates chose to consider a single point then concluding that the calculated <em>mr</em> would&nbsp;be smaller than the real value as <em>W</em> &lt; centripetal force, or even went into analysing the dependence of the&nbsp;frictional force with <em>W</em>. Many were able to deduce this. Some candidates thought that a graph would still&nbsp;have the same gradient (if friction was constant) and mentioned systematic error, so <em>mr</em> was not changed&nbsp;which was also accepted.</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Most candidates stated that the mean of 5 values of <em>T</em> was used to obtain an answer closer to the true&nbsp;value if there were no systematic errors. Some just repeated the question.</p>
<div class="question_part_label">c(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Usually very well answered acknowledging that systematic errors are constant and present throughout all&nbsp; measurements.</p>
<div class="question_part_label">c(ii).</div>
</div>
<br><hr><br><div class="specification">
<p>A student carries out an experiment to determine the variation of intensity of the light with&nbsp;distance from a point light source. The light source is at the centre of a transparent spherical&nbsp;cover of radius <em>C</em>. The student measures the distance <em>x </em>from the surface of the cover to a&nbsp;sensor that measures the intensity <em>I </em>of the light.</p>
<p style="text-align: center;"><img src="images/Schermafbeelding_2018-08-12_om_15.49.35.png" alt="M18/4/PHYSI/SP3/ENG/TZ2/02"></p>
<p>The light source emits radiation with a constant power <em>P </em>and all of this radiation is&nbsp;transmitted through the cover. The relationship between <em>I </em>and <em>x </em>is given by</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="I = \frac{P}{{4\pi {{(C + x)}^2}}}">
  <mi>I</mi>
  <mo>=</mo>
  <mfrac>
    <mi>P</mi>
    <mrow>
      <mn>4</mn>
      <mi>π<!-- π --></mi>
      <mrow>
        <msup>
          <mrow>
            <mo stretchy="false">(</mo>
            <mi>C</mi>
            <mo>+</mo>
            <mi>x</mi>
            <mo stretchy="false">)</mo>
          </mrow>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span></p>
</div>

<div class="specification">
<p>The student obtains a set of data and uses this to plot a graph of the variation of&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{{\sqrt I }}">
  <mfrac>
    <mn>1</mn>
    <mrow>
      <msqrt>
        <mi>I</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span>&nbsp;with <em>x</em>.</p>
<p style="text-align: left;"><img src="data:image/png;base64,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"></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>This relationship can also be written as follows.</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="\frac{1}{{\sqrt I }} = Kx + KC">
  <mfrac>
    <mn>1</mn>
    <mrow>
      <msqrt>
        <mi>I</mi>
      </msqrt>
    </mrow>
  </mfrac>
  <mo>=</mo>
  <mi>K</mi>
  <mi>x</mi>
  <mo>+</mo>
  <mi>K</mi>
  <mi>C</mi>
</math></span></p>
<p>Show that&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="K = 2\sqrt {\frac{\pi }{P}} ">
  <mi>K</mi>
  <mo>=</mo>
  <mn>2</mn>
  <msqrt>
    <mfrac>
      <mi>π</mi>
      <mi>P</mi>
    </mfrac>
  </msqrt>
</math></span>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Estimate <em>C</em>.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Determine <em>P</em>, to the correct number of significant figures including its unit.</p>
<div class="marks">[4]</div>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Explain the disadvantage that a graph of <em>I </em>versus <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{{{x^2}}}">
  <mfrac>
    <mn>1</mn>
    <mrow>
      <mrow>
        <msup>
          <mi>x</mi>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span>&nbsp;has for the analysis in&nbsp;(b)(i) and (b)(ii).</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>combines the two equations to obtain result</p>
<p>&nbsp;</p>
<p><strong>«</strong>for example&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{I}">
  <mfrac>
    <mn>1</mn>
    <mi>I</mi>
  </mfrac>
</math></span> =&nbsp;<em>K</em><sup>2</sup>(<em>C</em> +&nbsp;<em>x</em>)<sup>2</sup> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{4\pi }}{P}">
  <mfrac>
    <mrow>
      <mn>4</mn>
      <mi>π</mi>
    </mrow>
    <mi>P</mi>
  </mfrac>
</math></span>(<em>C</em> + <em>x</em>)<sup>2</sup><strong>»</strong></p>
<p><strong><em>OR</em></strong></p>
<p>reverse engineered solution – substitute&nbsp;<em>K</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="2\sqrt {\frac{\pi }{P}} ">
  <mn>2</mn>
  <msqrt>
    <mfrac>
      <mi>π</mi>
      <mi>P</mi>
    </mfrac>
  </msqrt>
</math></span>&nbsp;into <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{I}">
  <mfrac>
    <mn>1</mn>
    <mi>I</mi>
  </mfrac>
</math></span> = <em>K</em><sup>2</sup>(<em>C</em> +&nbsp;<em>x</em>)<sup>2</sup>&nbsp;to get <em>I</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{P}{{4\pi {{(C + x)}^2}}}">
  <mfrac>
    <mi>P</mi>
    <mrow>
      <mn>4</mn>
      <mi>π</mi>
      <mrow>
        <msup>
          <mrow>
            <mo stretchy="false">(</mo>
            <mi>C</mi>
            <mo>+</mo>
            <mi>x</mi>
            <mo stretchy="false">)</mo>
          </mrow>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span></p>
<p>&nbsp;</p>
<p><em>There are many ways to answer the question, look for a combination of two equations to obtain the third one</em></p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>extrapolating line to cross <em>x</em>-axis / use of <em>x</em>-intercept</p>
<p><strong><em>OR</em></strong></p>
<p>Use <em>C</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{y{\text{ - intercept}}}}{{{\text{gradient}}}}">
  <mfrac>
    <mrow>
      <mi>y</mi>
      <mrow>
        <mtext>&nbsp;- intercept</mtext>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <mtext>gradient</mtext>
      </mrow>
    </mrow>
  </mfrac>
</math></span></p>
<p><strong><em>OR</em></strong></p>
<p>use of gradient and one point, correctly substituted in one of the formulae</p>
<p>&nbsp;</p>
<p>accept answers between 3.0 and 4.5 <strong>«</strong>cm<strong>»</strong></p>
<p>&nbsp;</p>
<p><em>Award </em><strong><em>[1 max] </em></strong><em>for negative answers</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><strong><em>ALTERNATIVE 1</em></strong></p>
<p>Evidence of finding gradient using two points on the line at least 10 cm apart</p>
<p>Gradient found in range: 115–135 <strong><em>or </em></strong>1.15–1.35</p>
<p>Using <em>P</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{4\pi }}{{{K^2}}}">
  <mfrac>
    <mrow>
      <mn>4</mn>
      <mi>π</mi>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mi>K</mi>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span>&nbsp;to get value between 6.9 × 10<sup>–4</sup> and 9.5 × 10<sup>–4</sup>&nbsp;<strong>«</strong>W<strong>»</strong>&nbsp;and POT correct</p>
<p>Correct unit, W <strong>and </strong>answer to 1, 2 or 3 significant figures</p>
<p>&nbsp;</p>
<p><strong><em>ALTERNATIVE 2</em></strong></p>
<p>Finds <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="I\left( {\frac{1}{{{y^2}}}} \right)">
  <mi>I</mi>
  <mrow>
    <mo>(</mo>
    <mrow>
      <mfrac>
        <mn>1</mn>
        <mrow>
          <mrow>
            <msup>
              <mi>y</mi>
              <mn>2</mn>
            </msup>
          </mrow>
        </mrow>
      </mfrac>
    </mrow>
    <mo>)</mo>
  </mrow>
</math></span> from use of one point (<em>x </em>and <em>y</em>) on the line with <em>x</em> &gt; 6 cm&nbsp;and <em>C</em> from(b)(i)to use in <em>I</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{P}{{4\pi {{(C + x)}^2}}}">
  <mfrac>
    <mi>P</mi>
    <mrow>
      <mn>4</mn>
      <mi>π</mi>
      <mrow>
        <msup>
          <mrow>
            <mo stretchy="false">(</mo>
            <mi>C</mi>
            <mo>+</mo>
            <mi>x</mi>
            <mo stretchy="false">)</mo>
          </mrow>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span>&nbsp;or&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{{\sqrt I }}">
  <mfrac>
    <mn>1</mn>
    <mrow>
      <msqrt>
        <mi>I</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span> =&nbsp;<em>Kx</em>&nbsp;+&nbsp;<em>KC</em></p>
<p>Correct re-arrangementto get <em>P </em>between 6.9 × 10<sup>–4</sup> and 9.5 × 10<sup>–4</sup>&nbsp;<strong>«</strong>W<strong>»</strong> and POT correct</p>
<p>Correct unit, W <strong>and</strong>&nbsp;answer to 1, 2 or 3 significant figures</p>
<p>&nbsp;</p>
<p><em>Award </em><strong><em>[3 max] </em></strong><em>for an answer between 6.9 W and 9.5 W (POT penalized in 3rd marking point)</em></p>
<p><em>Alternative 2 is worth </em><strong><em>[3 max]</em></strong></p>
<p><strong><em>[4 marks]</em></strong></p>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>this graph will be a curve / not be a straight line</p>
<p>&nbsp;</p>
<p>more difficult to determine value of <em>K</em></p>
<p><strong><em>OR</em></strong></p>
<p>more difficult to determine value of <em>C</em></p>
<p><strong><em>OR</em></strong></p>
<p>suitable mathematical argument</p>
<p>&nbsp;</p>
<p><em>OWTTE</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<br><hr><br><div class="specification">
<p>In an experiment to measure the specific latent heat of vaporization of water <em>L</em><sub>v</sub>, a student&nbsp;uses an electric heater to boil water. A mass <em>m</em> of water vaporizes during time <em>t</em>. <em>L</em><sub>v</sub> may be&nbsp;calculated using the relation</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="{L_v} = \frac{{VIt}}{m}">
  <mrow>
    <msub>
      <mi>L</mi>
      <mi>v</mi>
    </msub>
  </mrow>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mi>V</mi>
      <mi>I</mi>
      <mi>t</mi>
    </mrow>
    <mi>m</mi>
  </mfrac>
</math></span></p>
<p>where <em>V</em> is the voltage applied to the heater and <em>I</em> the current through it.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Outline why, during the experiment, <em>V</em> and <em>I</em> should be kept constant.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Outline whether the value of <em>L</em><sub>v</sub> calculated in this experiment is expected to be larger or smaller than the actual value.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>A student suggests that to get a more accurate value of <em>L</em><sub>v</sub> the experiment should be performed twice using different heating rates. With voltage and current <em>V</em><sub>1</sub>, <em>I</em><sub>1</sub> the mass of water that vaporized in time <em>t</em> is <em>m</em><sub>1</sub>. With voltage and current <em>V</em><sub>2</sub>, <em>I</em><sub>2</sub> the mass of water that vaporized in time <em>t</em> is <em>m</em><sub>2</sub>. The student now uses the expression</p>
<p> </p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="{L_v} = \frac{{\left( {{V_1}{I_1} - {V_2}{I_2}} \right)t}}{{{m_1} - {m_2}}}">
  <mrow>
    <msub>
      <mi>L</mi>
      <mi>v</mi>
    </msub>
  </mrow>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mrow>
        <mo>(</mo>
        <mrow>
          <mrow>
            <msub>
              <mi>V</mi>
              <mn>1</mn>
            </msub>
          </mrow>
          <mrow>
            <msub>
              <mi>I</mi>
              <mn>1</mn>
            </msub>
          </mrow>
          <mo>−</mo>
          <mrow>
            <msub>
              <mi>V</mi>
              <mn>2</mn>
            </msub>
          </mrow>
          <mrow>
            <msub>
              <mi>I</mi>
              <mn>2</mn>
            </msub>
          </mrow>
        </mrow>
        <mo>)</mo>
      </mrow>
      <mi>t</mi>
    </mrow>
    <mrow>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>1</mn>
        </msub>
      </mrow>
      <mo>−</mo>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>2</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
</math></span></p>
<p> </p>
<p>to calculate <em>L</em><sub>v</sub>. Suggest, by reference to heat losses, why this is an improvement.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>to provide a constant heating rate / power</p>
<p><em><strong>OR</strong></em></p>
<p>to have <em>m</em> proportional to <em>t</em> ✔</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>due to heat losses «<em>VIt</em> is larger than heat into liquid» ✔</p>
<p><em>L</em><sub>v</sub> calculated will be larger ✔</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>heat losses will be similar / the same for both experiments</p>
<p><em><strong>OR</strong></em></p>
<p>heat loss presents systematic error ✔</p>
<p> </p>
<p>taking the difference cancels/eliminates the effect of these losses</p>
<p><em><strong>OR</strong></em></p>
<p>use a graph to eliminate the effect ✔</p>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<br><hr><br><div class="specification">
<p>An experiment to find the internal resistance of a cell of known emf is to be set. The following equipment is available:</p>
<p style="text-align: center;"><img src="images/Schermafbeelding_2018-08-11_om_06.19.36.png" alt="M18/4/PHYSI/SP3/ENG/TZ1/02"></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Draw a suitable circuit diagram that would enable the internal resistance to be determined.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>It is noticed that the resistor gets warmer. Explain how this would affect the calculated value of the internal resistance.</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Outline how using a variable resistance could improve the accuracy of the value found for the internal resistance.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><img src="images/Schermafbeelding_2018-08-11_om_07.22.52.png" alt="M18/4/PHYSI/SP3/ENG/TZ1/02.a/M"></p>
<p>ammeter and resistor in series</p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>resistance of resistor would increase / be greater than 10 Ω</p>
<p><em>R </em>+ <em>r </em><strong>«</strong>from <em>ε</em>&nbsp;= <em><strong>I</strong></em>(<em>R</em>&nbsp;+ <em>r</em>)<strong>» </strong>would be overestimated / lower current</p>
<p>therefore calculated <em>r </em>would be larger than real</p>
<p>&nbsp;</p>
<p><em>Award MP3 only if at least one previous mark has been awarded.</em></p>
<p><strong><em>[3 marks]</em></strong></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>variable resistor would allow for multiple readings to be made</p>
<p>gradient of V-I graph could be found <strong>«</strong>to give <em>r</em><strong>»</strong></p>
<p>&nbsp;</p>
<p><em>Award </em><strong><em>[1 max] </em></strong><em>for taking average of multiple.</em></p>
<p><strong><em>[2 marks]</em></strong></p>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<br><hr><br><div class="specification">
<p>A magnetized needle is oscillating on a string about a vertical axis in a horizontal magneticfield <em>B</em>. The time for 10 oscillations is recorded for different values of <em>B</em>.</p>
<p style="text-align: center;"><img src="images/Schermafbeelding_2018-08-11_om_06.15.15.png" alt="M18/4/PHYSI/SP3/ENG/TZ1/01_01"></p>
<p>The graph shows the variation with <em>B </em>of the time for 10 oscillations together with the uncertainties in the time measurements. The uncertainty in <em>B </em>is negligible.</p>
<p style="text-align: left;"><img src="data:image/png;base64,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"></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Draw on the graph the line of best fit for the data.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Write down the time taken for one oscillation when <em>B </em>= 0.005 T with its absolute uncertainty.</p>
<div class="marks">[1]</div>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>A student forms a hypothesis that the period of one oscillation <em>P </em>is given by:</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="P = \frac{K}{{\sqrt B }}">
  <mi>P</mi>
  <mo>=</mo>
  <mfrac>
    <mi>K</mi>
    <mrow>
      <msqrt>
        <mi>B</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span></p>
<p>where <em>K </em>is a constant.</p>
<p>Determine the value of <em>K </em>using the point for which <em>B </em>= 0.005 T.</p>
<p>State the uncertainty in <em>K </em>to an appropriate number of significant figures.&nbsp;</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State the unit of <em>K</em>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">b.iii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The student plots a graph to show how <em>P</em><sup>2</sup> varies with <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{B}">
  <mfrac>
    <mn>1</mn>
    <mi>B</mi>
  </mfrac>
</math></span>&nbsp;for the data.</p>
<p>Sketch the shape of the expected line of best fit on the axes below assuming that the relationship <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="P = \frac{K}{{\sqrt B }}">
  <mi>P</mi>
  <mo>=</mo>
  <mfrac>
    <mi>K</mi>
    <mrow>
      <msqrt>
        <mi>B</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span>&nbsp;is verified. You do <strong>not </strong>have to put numbers on the axes.</p>
<p><img src="data:image/png;base64,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"></p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State how the value of <em>K </em>can be obtained from the graph.</p>
<div class="marks">[1]</div>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>smooth line, not kinked, passing through all the error bars.</p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>0.84 ± 0.03&nbsp;<strong>«</strong>s<strong>»</strong></p>
<p>&nbsp;</p>
<p><em>Accept any value from the range: 0.81 to 0.87.</em></p>
<p><em>Accept uncertainty 0.03 </em><strong><em>OR </em></strong><em>0.025.</em></p>
<p><strong><em>[1 mark]</em></strong></p>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="K = \sqrt {0.005} &nbsp;\times 0.84 = 0.059">
  <mi>K</mi>
  <mo>=</mo>
  <msqrt>
    <mn>0.005</mn>
  </msqrt>
  <mo>×</mo>
  <mn>0.84</mn>
  <mo>=</mo>
  <mn>0.059</mn>
</math></span></p>
<p><strong>«</strong><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{\Delta K}}{K} = \frac{{\Delta P}}{P}">
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>K</mi>
    </mrow>
    <mi>K</mi>
  </mfrac>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>P</mi>
    </mrow>
    <mi>P</mi>
  </mfrac>
</math></span><strong>»</strong></p>
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\Delta K = \frac{{0.03}}{{0.84}} \times 0.0594 = 0.002">
  <mi mathvariant="normal">Δ</mi>
  <mi>K</mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>0.03</mn>
    </mrow>
    <mrow>
      <mn>0.84</mn>
    </mrow>
  </mfrac>
  <mo>×</mo>
  <mn>0.0594</mn>
  <mo>=</mo>
  <mn>0.002</mn>
</math></span></p>
<p><strong>«</strong><em>K =</em>(0.059 ± 0.002)<strong>»</strong>&nbsp;</p>
<p>uncertainty given to 1sf</p>
<p>&nbsp;</p>
<p><em>Allow ECF </em><strong><em>[3 max] </em></strong><em>if 10T is used.</em></p>
<p><em>Award </em><strong><em>[3] </em></strong><em>for BCA.</em></p>
<p><strong><em>[3 marks]</em></strong></p>
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\text{s}}{{\text{T}}^{\frac{1}{2}}}">
  <mrow>
    <mtext>s</mtext>
  </mrow>
  <mrow>
    <msup>
      <mrow>
        <mtext>T</mtext>
      </mrow>
      <mrow>
        <mfrac>
          <mn>1</mn>
          <mn>2</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span></p>
<p>&nbsp;</p>
<p><em>Accept </em><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="s\sqrt T ">
  <mi>s</mi>
  <msqrt>
    <mi>T</mi>
  </msqrt>
</math></span><em>&nbsp;</em>or in words.</p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">b.iii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>straight <strong><em>AND </em></strong>ascending line</p>
<p>through origin</p>
<p><em><strong>[2 marks]</strong></em></p>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="K = \sqrt {{\text{slope}}} ">
  <mi>K</mi>
  <mo>=</mo>
  <msqrt>
    <mrow>
      <mtext>slope</mtext>
    </mrow>
  </msqrt>
</math></span></p>
<p><em><strong>[1 mark]</strong></em></p>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.iii.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">d.</div>
</div>
<br><hr><br><div class="specification">
<p><span style="background-color: #ffffff;">The resistance<em> R</em> of a wire of length <em>L</em> can be measured using the circuit shown.</span></p>
<p style="text-align: center;"><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></p>
</div>

<div class="specification">
<p><span style="background-color: #ffffff;">In one experiment the wire has a uniform diameter of <em>d</em> = 0.500 mm. The graph shows data obtained for the variation of <em>R</em> with <em>L</em>.</span></p>
<p><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The gradient of the line of best fit is 6.30 Ω m<sup>–1</sup>.</span></span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">Estimate the resistivity of the material of the wire. Give your answer to an appropriate number of significant figures.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">a(i).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">Explain, by reference to the power dissipated in the wire, the advantage of the fixed resistor connected in series with the wire for the measurement of<em> R</em>.</span></p>
<div class="marks">[3]</div>
<div class="question_part_label">a(ii).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">The experiment is repeated using a wire made of the same material but of a larger diameter than the wire in part (a). On the axes in part (a), draw the graph for this second experiment.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span style="background-color: #ffffff;">evidence of use of<em> ρ</em> = given gradient × wire area<br><em><strong>OR</strong></em><br>substitution of values from a single data point with wire area ✔</span></p>
<p><span style="background-color: #ffffff;"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>ρ</mi><mo>=</mo><mo>«</mo><mo>=</mo><mn>6</mn><mo>.</mo><mn>30</mn><mo>×</mo><mi mathvariant="normal">π</mi><mo>×</mo><msup><mfenced><mfrac><mrow><mn>0</mn><mo>.</mo><mn>500</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>-</mo><mn>3</mn></mrow></msup></mrow><mn>2</mn></mfrac></mfenced><mn>2</mn></msup><mo>=</mo><mo>»</mo><mn>1</mn><mo>.</mo><mn>24</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>-</mo><mn>6</mn></mrow></msup><mo> </mo><mo>«</mo><mtext>Ω  m</mtext><mo>»</mo></math><span style="display: inline !important;float: none;background-color: #ffffff;color: #000000;font-family: Verdana,Arial,Helvetica,sans-serif;font-size: 14px;font-style: normal;font-variant: normal;font-weight: 400;letter-spacing: normal;text-align: left;text-decoration: none;text-indent: 0px;white-space: normal;">✔</span></span></p>
<p><em><span style="background-color: #ffffff;">NOTE: Check POT is correct. <br>MP2 must be correct to exactly 3 s.f.</span></em></p>
<div class="question_part_label">a(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span style="background-color: #ffffff;">measurement should be performed at a constant temperature<br><em><strong>OR</strong></em><br>resistance of wire changes with temperature ✔</span></p>
<p><span style="background-color: #ffffff;">series resistance prevents the wire from overheating<br><em><strong>OR</strong></em><br>reduces power dissipated in the wire ✔</span></p>
<p><span style="background-color: #ffffff;">by reducing voltage across/current through the wire ✔</span></p>
<div class="question_part_label">a(ii).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span style="background-color: #ffffff;">ANY straight line going through the origin if extrapolated ✔<br>ANY straight line below existing line with smaller gradient ✔</span></p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a(ii).</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="specification">
<p>In an investigation to measure the acceleration of free fall a rod is suspended horizontally by&nbsp;two vertical strings of equal length. The strings are a distance<em> d</em> apart.</p>
<p style="text-align: center;"><img src="data:image/png;base64,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"></p>
<p>When the rod is displaced by a small angle and then released, simple harmonic oscillations&nbsp;take place in a horizontal plane.</p>
<p>The theoretical prediction for the period of oscillation<em> T</em> is given by the following equation</p>
<p style="text-align: center;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="T = \frac{c}{{d\sqrt g }}">
  <mi>T</mi>
  <mo>=</mo>
  <mfrac>
    <mi>c</mi>
    <mrow>
      <mi>d</mi>
      <msqrt>
        <mi>g</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span></p>
<p>where <em>c</em> is a known numerical constant.</p>
</div>

<div class="specification">
<p>In one experiment <em>d</em> was varied. The graph shows the plotted values of <em>T</em> against&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{1}{d}">
  <mfrac>
    <mn>1</mn>
    <mi>d</mi>
  </mfrac>
</math></span>.&nbsp;Error bars are negligibly small.</p>
<p><img 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"></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>State the unit of <em>c</em>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>A student records the time for 20 oscillations of the rod. Explain how this procedure leads to a more precise measurement of the time for <strong>one</strong> oscillation <em>T</em>.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Draw the line of best fit for these data.</p>
<div class="marks">[1]</div>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Suggest whether the data are consistent with the theoretical prediction.</p>
<div class="marks">[2]</div>
<div class="question_part_label">c.ii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>The numerical value of the constant <em>c</em> in SI units is 1.67. Determine <em>g</em>, using the graph.</p>
<div class="marks">[4]</div>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{m^{\frac{3}{2}}}">
  <mrow>
    <msup>
      <mi>m</mi>
      <mrow>
        <mfrac>
          <mn>3</mn>
          <mn>2</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span>&nbsp;✔</p>
<p>&nbsp;</p>
<p><em>Accept other power of tens multiples of&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{m^{\frac{3}{2}}}">
  <mrow>
    <msup>
      <mi>m</mi>
      <mrow>
        <mfrac>
          <mn>3</mn>
          <mn>2</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span>, eg:&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{cm^{\frac{3}{2}}}">
  <mrow>
    <mi>c</mi>
    <msup>
      <mi>m</mi>
      <mrow>
        <mfrac>
          <mn>3</mn>
          <mn>2</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span>.</em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>measured uncertainties «for one oscillation and for 20 oscillations» are the same/similar/OWTTE</p>
<p><em><strong>OR</strong></em></p>
<p>% uncertainty is less for 20 oscillations than for one ✔</p>
<p> </p>
<p>dividing «by 20» / finding mean reduces the random error ✔</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Straight line touching at least 3 points drawn across the range ✔</p>
<p><img 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"></p>
<p><em>It is not required to extend the line to pass through the origin.</em></p>
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>theory predicts proportional relation «<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="T \propto \frac{1}{d}">
  <mi>T</mi>
  <mo>∝</mo>
  <mfrac>
    <mn>1</mn>
    <mi>d</mi>
  </mfrac>
</math></span>, slope = <em>Td&nbsp;</em>=&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{c}{{\sqrt g }}">
  <mfrac>
    <mi>c</mi>
    <mrow>
      <msqrt>
        <mi>g</mi>
      </msqrt>
    </mrow>
  </mfrac>
</math></span> = constant » ✔</p>
<p>the graph is «straight» line <span style="text-decoration: underline;">through the origin</span> ✔</p>
<div class="question_part_label">c.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>correctly determines gradient using points where ΔT≥1.5s</p>
<p><em><strong>OR</strong></em></p>
<p>correctly selects a single data point with T≥1.5s ✔</p>
<p> </p>
<p>manipulation with formula, any new and correct expression to enable g to be determined ✔</p>
<p>Calculation of g ✔</p>
<p>With g in range 8.6 and 10.7 «m s<sup>−2</sup>» ✔</p>
<p> </p>
<p><em>Allow range 0.51 to 0.57.</em></p>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">d.</div>
</div>
<br><hr><br><div class="specification">
<p><span style="background-color: #ffffff;">A student investigates how the period<em> T</em> of a simple pendulum varies with the maximum speed <em>v</em> of the pendulum’s bob by releasing the pendulum from rest from different initial angles. A graph of the variation of <em>T</em> with <em>v</em> is plotted.</span></p>
<p><span style="background-color: #ffffff;"><img 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"></span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">Suggest, by reference to the graph, why it is unlikely that the relationship between <em>T</em> and <em>v</em> is linear.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">Determine the fractional uncertainty in <em>v</em> when <em>T</em> = 2.115 s, correct to <strong>one</strong> significant figure.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">The student hypothesizes that the relationship between <em>T</em> and <em>v</em> is <em>T = a + bv</em><sup>2</sup>, where <em>a</em> and <em>b</em> are constants. To verify this hypothesis a graph showing the variation of <em>T</em> with <em>v</em><sup>2</sup> is plotted. The graph shows the data and the line of best fit.</span></p>
<p><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">Determine <em>b</em>, giving an appropriate unit for <em>b</em>.</span></span></p>
<div class="marks">[3]</div>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color: #ffffff;">The lines of the minimum and maximum gradient are shown.</span></p>
<p><span style="background-color: #ffffff;"><img 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"></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">Estimate the absolute uncertainty in <em>a</em>.</span></span></p>
<div class="marks">[2]</div>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span style="background-color: #ffffff;">a straight line cannot be drawn through all error bars<br><em><strong>OR</strong></em><br>the graph/line of best fit is /curved/not straight/parabolic etc.<br><em><strong>OR</strong></em><br>graph has increasing/variable gradient ✔</span></p>
<p><em><span style="background-color: #ffffff;">NOTE: Do not allow “a line cannot be drawn through all error bars” without specifying “straight”.</span></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span style="background-color: #ffffff;"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>v</mi><mo>=</mo><mn>1</mn><mo>.</mo><mn>15</mn><mo> </mo><mo>«</mo><mi mathvariant="normal">m</mi><mo> </mo><mo> </mo><msup><mi mathvariant="normal">s</mi><mrow><mo>-</mo><mn>1</mn></mrow></msup><mo>»</mo></math>  <em><strong>AND </strong></em> <math xmlns="http://www.w3.org/1998/Math/MathML"><mo>∆</mo><mi>v</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>05</mn><mo> </mo><mo>«</mo><mi mathvariant="normal">m</mi><mo> </mo><mo> </mo><msup><mi mathvariant="normal">s</mi><mrow><mo>-</mo><mn>1</mn></mrow></msup><mo>»</mo></math> ✔</span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">«<math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mrow><mn>0</mn><mo>.</mo><mn>05</mn></mrow><mrow><mn>1</mn><mo>.</mo><mn>15</mn></mrow></mfrac><mo>=</mo></math>»0.04 <span style="display: inline !important;float: none;background-color: #ffffff;color: #000000;font-family: Verdana,Arial,Helvetica,sans-serif;font-size: 14px;font-style: normal;font-variant: normal;font-weight: 400;letter-spacing: normal;text-align: left;text-decoration: none;text-indent: 0px;white-space: normal;">✔</span></span></span></p>
<p><em><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">NOTE: Accept 4 %</span></span></em></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>use of 2 correct points on the line with Δ<em>v</em><sup>2 </sup>&gt; 2 ✔</p>
<p><em>b</em> in range 0.012 to 0.013 ✔</p>
<p>s<sup>3 </sup>m<sup>–2 </sup>✔</p>
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>a</mi><mi>max</mi></msub><mo>=</mo><mn>2</mn><mo>.</mo><mn>101</mn></math> «s» ±0.001 «s» <em><strong>AND</strong></em> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>a</mi><mi>min</mi></msub><mo>=</mo><mn>2</mn><mo>.</mo><mn>095</mn></math>«s» ±0.001 «s» ✔</p>
<p>«<math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mrow><mn>2</mn><mo>.</mo><mn>101</mn><mo>-</mo><mn>2</mn><mo>.</mo><mn>095</mn></mrow><mn>2</mn></mfrac><mo>=</mo></math>» 0.003 «s» ✔</p>
<div class="question_part_label">d.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">d.</div>
</div>
<br><hr><br><div class="specification">
<p>In an experiment to measure the acceleration of free fall a student ties two different blocks of masses <em>m</em><sub>1</sub> and <em>m</em><sub>2</sub> to the ends of a string that passes over a frictionless pulley.</p>
<p style="text-align: center;"><img src="data:image/png;base64,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"></p>
<p style="text-align: left;">The student calculates the acceleration <em>a</em> of the blocks by measuring the time taken by the heavier mass to fall through a given distance. Their theory predicts that<em>&nbsp;</em><span style="background-color: #ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="a = g\frac{{{m_1} - {m_2}}}{{{m_1} + {m_2}}}">
  <mi>a</mi>
  <mo>=</mo>
  <mi>g</mi>
  <mfrac>
    <mrow>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>1</mn>
        </msub>
      </mrow>
      <mo>−<!-- − --></mo>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>2</mn>
        </msub>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>1</mn>
        </msub>
      </mrow>
      <mo>+</mo>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>2</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
</math></span></span> and this can be re-arranged to give&nbsp;<span style="background-color: #ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="g = a\frac{{{m_1} + {m_2}}}{{{m_1} - {m_2}}}">
  <mi>g</mi>
  <mo>=</mo>
  <mi>a</mi>
  <mfrac>
    <mrow>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>1</mn>
        </msub>
      </mrow>
      <mo>+</mo>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>2</mn>
        </msub>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>1</mn>
        </msub>
      </mrow>
      <mo>−<!-- − --></mo>
      <mrow>
        <msub>
          <mi>m</mi>
          <mn>2</mn>
        </msub>
      </mrow>
    </mrow>
  </mfrac>
</math></span>.</span></p>
<p style="text-align: left;">In a particular experiment the student calculates that <em>a</em> = (0.204 ±0.002) ms<sup>–2</sup> using <em>m</em><sub>1</sub> = (0.125 ±0.001) kg and <em>m</em><sub>2</sub> = (0.120 ±0.001) kg.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Calculate the percentage error in the measured value of <em>g</em>.</p>
<div class="marks">[3]</div>
<div class="question_part_label">a.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Deduce the value of <em>g</em> and its absolute uncertainty for this experiment.</p>
<div class="marks">[2]</div>
<div class="question_part_label">a.ii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>There is an advantage and a disadvantage in using two masses that are almost equal.</p>
<p>State and explain the advantage with reference to the magnitude of the acceleration that is obtained.</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>There is an advantage and a disadvantage in using two masses that are almost equal.</p>
<p>State and explain the disadvantage with reference to your answer to (a)(ii).</p>
<div class="marks">[2]</div>
<div class="question_part_label">b.ii.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>error in <em>m</em><sub>1</sub> + <em>m</em><sub>2</sub> is 1 % <em><strong>OR</strong></em> error in <em>m</em><sub>1</sub> −&nbsp;<em>m</em><sub>2</sub>&nbsp;is 40 % <em><strong>OR</strong></em> error in <em>a</em> is 1 % ✔</p>
<p>adds percentage errors ✔</p>
<p>so error in g is 42 % <em><strong>OR</strong></em> 40 % <em><strong>OR</strong></em> 41.8 % ✔</p>
<p><em>Allow answer 0.42 or 0.4 or 0.418. </em></p>
<p><em>Award <strong>[0]</strong> for comparing the average value with a known value, e.g. 9.81 m s-2</em>.</p>
<div class="question_part_label">a.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><em>g</em> = 9.996&nbsp;«m s<sup>−2</sup>» <em><strong>OR</strong></em> Δ<em>g = </em>4.20 «m s<sup>−2</sup>» ✔</p>
<p><em>g</em>&nbsp;= (10 ± 4) «m s<sup>−2</sup>»</p>
<p><em><strong>OR</strong></em></p>
<p><em>g</em>&nbsp;= (10.0 ± 4.2) «m s<sup>−2</sup>»&nbsp;✔</p>
<p><em>Award <strong>[1]</strong> max for not proper significant digits or decimals use, such as: 9.996±4.178 or 10±4.2 or 10.0±4 or 10.0±4.18« m s<sup>−2</sup> »</em> .</p>
<div class="question_part_label">a.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>the acceleration would be small/the time of fall would be large ✔</p>
<p>easier to measure /a longer time of fall reduces the % error in the time of fall and «hence acceleration» ✔</p>
<p><em>Do not accept ideas related to the mass/moment of inertia of the pulley</em>.</p>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>the percentage error in the difference of the masses is large ✔</p>
<p>leading to a large percentage error/uncertainty in g/of the experiment ✔</p>
<p><em>Do not accept ideas related to the mass/moment of inertia of the pulley.</em></p>
<div class="question_part_label">b.ii.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Atwoods machine a) is a quite straightforward question that tests the ability to propagate uncertainties through calculations. Almost all candidates proved the ability to add percentages or relative calculations, however, many weaker candidates failed in the percentage uncertainty when subtracting the two masses.</p>
<div class="question_part_label">a.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Many average candidates did not use the correct number of significant figures and wrote the answers inappropriately. Only the best candidates rounded out and wrote the proper answer of 10±4 ms<sup>−2</sup>. Some candidates did not propagate uncertainties and only compared the average calculated value with the known value 9.81 ms<sup>−2</sup>.</p>
<div class="question_part_label">a.ii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Q 1 b) was quite well answered. Only the weakest candidates presented difficulty in understanding simple mechanics.</p>
<div class="question_part_label">b.i.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>In part ii) many were able to appreciate that the resultant percentage error in “g” was relatively large however linking this with what caused the large uncertainty (that is, the high % error from the small difference in masses) proved more challenging.</p>
<div class="question_part_label">b.ii.</div>
</div>
<br><hr><br><div class="specification">
<p>A student measures the refractive index of water by shining a light ray into a transparent container.</p>
<p>IO shows the direction of the normal at the point where the light is incident on the container. IX shows the direction of the light ray when the container is empty. IY shows the direction of the deviated light ray when the container is filled with water.</p>
<p>The angle of incidence&nbsp;<em>θ</em> is varied and the student determines the position of O, X and Y for each angle of incidence.</p>
<p style="text-align: center;"><img 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"></p>
<p>The table shows the data collected by the student. The uncertainty in each measurement of length is ±0.1 cm.</p>
<p style="text-align: center;"><img 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"></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>(i) Outline why OY has a greater percentage uncertainty than OX for each pair of data points.</p>
<p>(ii) The refractive index of the water is given by <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{{\rm{OX}}}}{{{\rm{OY}}}}">
  <mfrac>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">X</mi>
        </mrow>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">Y</mi>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span>when OX is small.</p>
<p>Calculate the fractional uncertainty in the value of the refractive index of water for OX = 1.8 cm.</p>
<div class="marks">[3]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>A graph of the variation of OY with OX is plotted.<img src="data:image/png;base64,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"></p>
<p>(i) Draw, on the graph, the error bars for OY when OX = 1.8 cm <strong>and</strong> when OY = 5.8 cm.</p>
<p>(ii) Determine, using the graph, the refractive index of the water in the container for values of OX less than 6.0 cm.</p>
<p>(iii) The refractive index for a material is also given by <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{\sin i}}{{\sin r}}">
  <mfrac>
    <mrow>
      <mi>sin</mi>
      <mo>⁡</mo>
      <mi>i</mi>
    </mrow>
    <mrow>
      <mi>sin</mi>
      <mo>⁡</mo>
      <mi>r</mi>
    </mrow>
  </mfrac>
</math></span> where <em>i</em> is the angle of incidence and <em>r</em> is the angle of refraction.</p>
<p>Outline why the graph deviates from a straight line for large values of OX.</p>
<div class="marks">[5]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>i<br>OY always smaller than OX <em><strong>AND</strong></em> uncertainties are the same/0.1<br>« so fraction <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{0.1}}{{{\rm{OY}}}} &gt; \frac{{0.1}}{{{\rm{OX}}}}">
  <mfrac>
    <mrow>
      <mn>0.1</mn>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">Y</mi>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
  <mo>&gt;</mo>
  <mfrac>
    <mrow>
      <mn>0.1</mn>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">X</mi>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span> »</p>
<p>ii<br><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{0.1}}{{{\rm{1.3}}}}">
  <mfrac>
    <mrow>
      <mn>0.1</mn>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mn>1.3</mn>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span> <em><strong>AND</strong></em> <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{0.1}}{{{\rm{1.8}}}}">
  <mfrac>
    <mrow>
      <mn>0.1</mn>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mn>1.8</mn>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span><br>= 0.13 <em><strong>OR</strong></em> 13%</p>
<p><em>Watch for correct answer even if calculation continues to the absolute uncertainty.</em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>i</p>
<p>total length of bar = 0.2 cm</p>
<p><em>Accept correct error bar in one of the points: OX= 1.8 cm <strong>OR</strong> OY= 5.8 cm (which is not a measured point but is a point on the interpolated line) <strong>OR</strong> OX= 5.8 cm. <br>Ignore error bar of OX.<br>Allow range from 0.2 to 0.3 cm, by eye.</em></p>
<p> </p>
<p>ii</p>
<p>suitable line drawn extending at least up to 6 cm<br><em><strong>OR<br></strong></em>gradient calculated using two out of the first three data points</p>
<p>inverse of slope used</p>
<p> </p>
<p>value between 1.30 and 1.60</p>
<p><em>If using one value of OX and OY from the graph for any of the first three data points award <strong>[2 max]</strong>.<br>Award [<strong>3</strong>] for correct value for each of the three data points and average.<br>If gradient used, award [<strong>1 max</strong>].</em></p>
<p> </p>
<p>iii</p>
<p>«the equation <em>n</em>=<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{{\rm{OX}}}}{{{\rm{OY}}}}">
  <mfrac>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">X</mi>
        </mrow>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">Y</mi>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span>» involves a tan approximation/is true only for small θ «when sinθ = tanθ»<br><em><strong>OR<br></strong></em>«the equation <em>n</em>=<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{{\rm{OX}}}}{{{\rm{OY}}}}">
  <mfrac>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">X</mi>
        </mrow>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <mrow>
          <mi mathvariant="normal">O</mi>
          <mi mathvariant="normal">Y</mi>
        </mrow>
      </mrow>
    </mrow>
  </mfrac>
</math></span>» uses OI instead of the hypotenuse of the ∆IOX or IOY</p>
<p><em>OWTTE</em></p>
<p> </p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="specification">
<p><span class="fontstyle0">A spherical soap bubble is made of a thin film of soapy water. The bubble has an internal air pressure <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>P</mi><mi mathvariant="normal">i</mi></msub></math></span><em><span class="fontstyle0">&nbsp;</span></em><span class="fontstyle0">and is formed in air of constant pressure </span><math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>P</mi><mi mathvariant="normal">o</mi></msub></math><span class="fontstyle0">. The theoretical prediction for the variation of <math xmlns="http://www.w3.org/1998/Math/MathML"><mfenced><mrow><msub><mi>P</mi><mtext>i</mtext></msub><mo>-</mo><msub><mi>P</mi><mtext>o</mtext></msub></mrow></mfenced></math></span><span class="fontstyle0">&nbsp;is given by the equation</span></p>
<p style="text-align: center;"><math xmlns="http://www.w3.org/1998/Math/MathML"><mo>(</mo><msub><mi>P</mi><mi mathvariant="normal">i</mi></msub><mo>-</mo><msub><mi>P</mi><mi mathvariant="normal">o</mi></msub><mo>)</mo><mo>=</mo><mfrac><mrow><mn>4</mn><mi mathvariant="normal">g</mi></mrow><mi>R</mi></mfrac></math></p>
<p style="text-align: left;"><span class="fontstyle0">where </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math> </span><span class="fontstyle0">is a constant for the thin film and </span><span class="fontstyle3"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>R</mi></math> </span><span class="fontstyle0">is the radius of the bubble.</span></p>
<p style="text-align: left;">Data for <math xmlns="http://www.w3.org/1998/Math/MathML"><mfenced><mrow><msub><mi>P</mi><mtext>i</mtext></msub><mo>-</mo><msub><mi>P</mi><mtext>o</mtext></msub></mrow></mfenced></math><span class="fontstyle0">&nbsp;and&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>R</mi></math>&nbsp; were collected under controlled conditions and plotted as a graph showing the variation of <math xmlns="http://www.w3.org/1998/Math/MathML"><mfenced><mrow><msub><mi>P</mi><mtext>i</mtext></msub><mo>-</mo><msub><mi>P</mi><mtext>o</mtext></msub></mrow></mfenced></math>&nbsp;with&nbsp;<math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mn>1</mn><mi>R</mi></mfrac></math>.<br> </span></p>
<p style="text-align: left;"><span class="fontstyle0"><img src="data:image/png;base64,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" width="788" height="662"></span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">Suggest whether the data are consistent with the theoretical prediction.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">Show that the value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math></span><span class="fontstyle2">  </span><span class="fontstyle0">is about 0.03.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">b(i).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">Identify the fundamental units of </span><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">b(ii).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">In order to find the uncertainty for </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math></span><span class="fontstyle0">, a maximum gradient line would be drawn. On the graph, sketch the maximum gradient line for the data.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">b(iii).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">The percentage uncertainty for <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math></span><span class="fontstyle2"> </span><span class="fontstyle0">is <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>15</mn><mo>%</mo></math>. State </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math></span><span class="fontstyle0">, with its absolute uncertainty.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">b(iv).</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span class="fontstyle0">The expected value of </span><span class="fontstyle2"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math> </span><span class="fontstyle0">is <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>027</mn></math>. Comment on your result</span>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">b(v).</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">«theory suggests» <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>P</mi><mi mathvariant="normal">i</mi></msub><mo>-</mo><msub><mi>P</mi><mi mathvariant="normal">o</mi></msub></math> </span><span class="fontstyle0">is proportional to <math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mn>1</mn><mi>R</mi></mfrac></math> </span><span class="fontstyle3">✓</span></p>
<p><span class="fontstyle3"><br></span><span class="fontstyle0">graph/line of best fit is straight/linear «so yes»<br></span><span class="fontstyle4"><em><strong>OR</strong></em><br></span><span class="fontstyle0">graph/line of best fit passes through the origin «so yes» </span><span class="fontstyle3">✓</span></p>
<p> </p>
<p><em><span class="fontstyle2">MP1: Accept ‘linear’<br></span></em></p>
<p><em><span class="fontstyle2">MP2 do not award if there is any contradiction<br>eg: graph not proportional, does not pass through origin.</span></em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">gradient <math xmlns="http://www.w3.org/1998/Math/MathML"><mo>=</mo></math> «<math xmlns="http://www.w3.org/1998/Math/MathML"><mn>4</mn><mi>γ</mi></math>» <math xmlns="http://www.w3.org/1998/Math/MathML"><mo>=</mo><mn>0</mn><mo>.</mo><mn>10</mn></math><br></span><span class="fontstyle2"><em><strong>OR</strong></em><br></span><span class="fontstyle0">use of equation with coordinates of a point </span><span class="fontstyle3">✓</span></p>
<p><span class="fontstyle3"><br></span><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>025</mn></math> <span class="fontstyle3">✓</span></p>
<p> </p>
<p><em><span class="fontstyle5">MP1 allow gradients in range <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>098</mn></math> to <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>102</mn></math><br></span></em></p>
<p><em><span class="fontstyle6">MP2 allow a range <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>024</mn></math> to <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>026</mn></math> for </span><span class="fontstyle4"><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>γ</mi></math></span></em></p>
<p> </p>
<div class="question_part_label">b(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><math xmlns="http://www.w3.org/1998/Math/MathML"><mi>kg</mi><mo> </mo><msup><mi mathvariant="normal">s</mi><mrow><mo>-</mo><mn>2</mn></mrow></msup></math> <span class="fontstyle2">✓</span></p>
<p> </p>
<p><em><span class="fontstyle3">Accept <math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mi>kg</mi><msup><mi mathvariant="normal">s</mi><mn>2</mn></msup></mfrac></math></span></em></p>
<p><span class="fontstyle3"> </span></p>
<div class="question_part_label">b(ii).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">straight line, gradient <strong>g</strong></span><span class="fontstyle2"><strong>reater</strong> </span><span class="fontstyle0">than line of best fit, and within the error bars </span><span class="fontstyle3">✓</span></p>
<p><span class="fontstyle3"><img src="data:image/png;base64,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"></span></p>
<div class="question_part_label">b(iii).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">«<math xmlns="http://www.w3.org/1998/Math/MathML"><mn>15</mn><mo>%</mo></math> of <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>025</mn></math>» = <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>00375</mn></math><br></span><span class="fontstyle2"><em><strong>OR</strong></em><br></span><span class="fontstyle0">«<math xmlns="http://www.w3.org/1998/Math/MathML"><mn>15</mn><mo>%</mo></math> of <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>030</mn></math>» = <math xmlns="http://www.w3.org/1998/Math/MathML"><mn>0</mn><mo>.</mo><mn>0045</mn></math> </span><span class="fontstyle3">✓<br></span></p>
<p><span class="fontstyle0">rounds uncertainty to 1sf<br><math xmlns="http://www.w3.org/1998/Math/MathML"><mo>±</mo><mn>0</mn><mo>.</mo><mn>004</mn></math><br></span><span class="fontstyle2"><em><strong>OR</strong></em><br></span><span class="fontstyle0"><math xmlns="http://www.w3.org/1998/Math/MathML"><mo>±</mo><mn>0</mn><mo>.</mo><mn>005</mn></math> </span><span class="fontstyle3">✓</span></p>
<p> </p>
<p><em><span class="fontstyle4">Allow ECF from (b)(i)<br>Award </span><strong><span class="fontstyle2">[2] </span></strong><span class="fontstyle4">marks for a bald correct answer</span></em></p>
<div class="question_part_label">b(iv).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><span class="fontstyle0">Experimental value matches this/correct, as expected value within the range </span><span class="fontstyle2">✓<br></span><span class="fontstyle3"><em><strong>OR</strong></em><br></span><span class="fontstyle0">experimental value does not match/incorrect, as it is not within range </span><span class="fontstyle2">✓</span></p>
<div class="question_part_label">b(v).</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Many students obtained full marks here although a significant number did not acknowledge that the&nbsp;graph was through the origin and lost a mark.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Very well answered either by obtaining the gradient or replacing with the coordinates of a point.</p>
<div class="question_part_label">b(i).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Although the question was specifically about the fundamental units, several candidates lost the mark by&nbsp;answering Pa m.</p>
<div class="question_part_label">b(ii).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Almost all candidates were able to draw the correct maximum gradient line.</p>
<div class="question_part_label">b(iii).</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Well answered. A significant number did not round the uncertainty to match the value of gamma.</p>
<div class="question_part_label">b(iv).</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b(v).</div>
</div>
<br><hr><br><div class="specification">
<p>To determine the acceleration due to gravity, a small metal sphere is dropped from rest and&nbsp;the time it takes to fall through a known distance and open a trapdoor is measured.</p>
<p style="text-align: center;"><img src="images/Schermafbeelding_2018-08-12_om_15.43.42.png" alt="M18/4/PHYSI/SP3/ENG/TZ2/01"></p>
<p>The following data are available.</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="\begin{array}{*{20}{l}} {{\text{Diameter of metal sphere}}}&amp;{ = 12.0 \pm 0.1{\text{ mm}}} \\ {{\text{Distance between the point of release and the trapdoor}}}&amp;{ = 654 \pm 2{\text{ mm}}} \\ {{\text{Measured time for fall}}}&amp;{ = 0.363 \pm 0.002{\text{ s}}} \end{array}">
  <mtable columnalign="left" rowspacing="4pt" columnspacing="1em">
    <mtr>
      <mtd>
        <mrow>
          <mrow>
            <mtext>Diameter of metal sphere</mtext>
          </mrow>
        </mrow>
      </mtd>
      <mtd>
        <mrow>
          <mo>=</mo>
          <mn>12.0</mn>
          <mo>±<!-- ± --></mo>
          <mn>0.1</mn>
          <mrow>
            <mtext>&nbsp;mm</mtext>
          </mrow>
        </mrow>
      </mtd>
    </mtr>
    <mtr>
      <mtd>
        <mrow>
          <mrow>
            <mtext>Distance between the point of release and the trapdoor</mtext>
          </mrow>
        </mrow>
      </mtd>
      <mtd>
        <mrow>
          <mo>=</mo>
          <mn>654</mn>
          <mo>±<!-- ± --></mo>
          <mn>2</mn>
          <mrow>
            <mtext>&nbsp;mm</mtext>
          </mrow>
        </mrow>
      </mtd>
    </mtr>
    <mtr>
      <mtd>
        <mrow>
          <mrow>
            <mtext>Measured time for fall</mtext>
          </mrow>
        </mrow>
      </mtd>
      <mtd>
        <mrow>
          <mo>=</mo>
          <mn>0.363</mn>
          <mo>±<!-- ± --></mo>
          <mn>0.002</mn>
          <mrow>
            <mtext>&nbsp;s</mtext>
          </mrow>
        </mrow>
      </mtd>
    </mtr>
  </mtable>
</math></span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Determine the distance fallen, in m, by the centre of mass of the sphere including an&nbsp;estimate of the absolute uncertainty in your answer.</p>
<div class="marks">[2]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Using the following equation</p>
<p><span class="mjpage mjpage__block"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block" alttext="{\text{acceleration due to gravity}} = \frac{{2 \times {\text{distance fallen by centre of mass of sphere}}}}{{{{{\text{(measured time to fall)}}}^{\text{2}}}}}">
  <mrow>
    <mtext>acceleration due to gravity</mtext>
  </mrow>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>2</mn>
      <mo>×</mo>
      <mrow>
        <mtext>distance fallen by centre of mass of sphere</mtext>
      </mrow>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mrow>
            <mrow>
              <mtext>(measured time to fall)</mtext>
            </mrow>
          </mrow>
          <mrow>
            <mtext>2</mtext>
          </mrow>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span></p>
<p>calculate, for these data, the acceleration due to gravity including an estimate of&nbsp;the absolute uncertainty in your answer.</p>
<div class="marks">[4]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>distance fallen = 654 – 12 = 642 <strong>«</strong>mm<strong>»</strong></p>
<p>absolute uncertainty<strong><em>&nbsp;</em></strong>= 2&nbsp;+&nbsp;0.1 <strong>«</strong>mm<strong>»</strong> ≈ 2 × 10<sup>–3</sup> <strong>«</strong>m<strong>»&nbsp;or</strong>&nbsp;= 2.1&nbsp;× 10<sup>–3</sup> <strong>«</strong>m<strong>»&nbsp;or</strong><strong>&nbsp;</strong>2.0&nbsp;× 10<sup>–3</sup> <strong>«</strong>m<strong>»</strong></p>
<p>&nbsp;</p>
<p><em>Accept answers in mm or m</em></p>
<p><strong><em>[2 marks]</em></strong><em>&nbsp;</em></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p><strong>«</strong><em>a</em> =&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{2s}}{{{t^2}}} = \frac{{2 \times 0.642}}{{{{0.363}^2}}}">
  <mfrac>
    <mrow>
      <mn>2</mn>
      <mi>s</mi>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mi>t</mi>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mn>2</mn>
      <mo>×</mo>
      <mn>0.642</mn>
    </mrow>
    <mrow>
      <mrow>
        <msup>
          <mrow>
            <mn>0.363</mn>
          </mrow>
          <mn>2</mn>
        </msup>
      </mrow>
    </mrow>
  </mfrac>
</math></span><strong>»</strong>&nbsp;= 9.744&nbsp;<strong>«</strong>ms<sup>–2</sup><strong>»</strong></p>
<p>fractional uncertainty in distance = <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{2}{{642}}">
  <mfrac>
    <mn>2</mn>
    <mrow>
      <mn>642</mn>
    </mrow>
  </mfrac>
</math></span> <em><strong>AND</strong></em> fractional uncertainty in time = <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{0.002}}{{0.363}}">
  <mfrac>
    <mrow>
      <mn>0.002</mn>
    </mrow>
    <mrow>
      <mn>0.363</mn>
    </mrow>
  </mfrac>
</math></span></p>
<p>total fractional uncertainty = <span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{\Delta s}}{s} + 2\frac{{\Delta t}}{t}">
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>s</mi>
    </mrow>
    <mi>s</mi>
  </mfrac>
  <mo>+</mo>
  <mn>2</mn>
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>t</mi>
    </mrow>
    <mi>t</mi>
  </mfrac>
</math></span>&nbsp;<strong>«</strong>= 0.00311 + 2&nbsp;×&nbsp;0.00551<strong>»</strong></p>
<p>total absolute uncertainty = 0.1 <em><strong>or</strong></em> 0.14 <em><strong>AND</strong></em> same number of decimal places in value and uncertainty, <em>ie</em>: 9.7 ± 0.1 <strong><em>or </em></strong>9.74 ± 0.14</p>
<p>&nbsp;</p>
<p><em>Accept working in %</em>&nbsp;<em>for MP2 and MP3</em></p>
<p><em>Final uncertainty must be the absolute uncertainty</em></p>
<p><strong><em>[4 marks]</em></strong></p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="specification">
<p><span style="background-color: #ffffff;">A student investigates the electromotive force (emf) <em>ε</em> and internal resistance<em> r</em> of a cell.</span></p>
<p><span style="background-color: #ffffff;"><img src="data:image/png;base64,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" width="213" height="196"></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The current <em>I</em> and the terminal potential difference <em>V</em> are measured.<br></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">For this circuit <em>V = ε - Ir</em> .<br></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The table shows the data collected by the student. The uncertainties for each measurement<br>are shown.</span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The graph shows the data plotted.</span></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;"><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></span></span></p>
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<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">The student has plotted error bars for the potential difference. Outline why no error bars are shown for the current.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Determine, using the graph, the emf of the cell including the uncertainty for this value. Give your answer to the correct number of significant figures.</span></p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Outline, <strong>without</strong> calculation, how the internal resistance can be determined from this graph.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">Δ<em>I</em> is too small to be shown/seen<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p><span style="background-color:#ffffff;">Error bar of negligible size compared to error bar in <em>V</em> ✔</span></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">evidence that ε can be determined from the y-intercept of the line of best-fit or lines of min and max gradient ✔<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">states ε=1.59 <em><strong>OR</strong></em> 1.60 <em><strong>OR</strong> </em>1.61V«» ✔<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">states uncertainty in ε is 0.02 V«» <em><strong>OR</strong></em> 0.03«V» ✔</span></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">determine the gradient «of the line of best-fit» ✔<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em>r</em> is the negative of this gradient ✔</span></p>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Almost all candidates realised that the uncertainty in I was too small to be shown. A common mistake was to mention that since I is the independent variable the uncertainty is negligible.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>The number of candidates who realised that the V intercept was EMF was disappointing. Large numbers of candidates tried to calculate ε using points on the graph, often ending up with unrealistic values. Another common mistake was not giving values of ε and Δε to the correct number of digits - 2 decimal places on this occasion. Very few candidates drew maximum and minimum gradient lines as a way of determining Δε.</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
[N/A]
<div class="question_part_label">c.</div>
</div>
<br><hr><br><div class="specification">
<p><span style="background-color: #ffffff;">A student uses a Young’s double-slit apparatus to determine the wavelength of light emitted by a monochromatic source. A portion of the interference pattern is observed on a screen.</span></p>
<p><span style="background-color: #ffffff;"><img src="data:image/png;base64,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"></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The distance <em>D</em> from the double slits to the screen is measured using a ruler with a smallest scale division of 1 mm.<br></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The fringe separation s is measured with uncertainty ± 0.1 mm.<br></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The slit separation d has negligible uncertainty.<br></span></span></p>
<p><span style="background-color: #ffffff;"><span style="background-color: #ffffff;">The wavelength is calculated using the relationship &nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\lambda&nbsp; = \frac{{sd}}{D}">
  <mi>λ<!-- λ --></mi>
  <mo>=</mo>
  <mfrac>
    <mrow>
      <mi>s</mi>
      <mi>d</mi>
    </mrow>
    <mi>D</mi>
  </mfrac>
</math></span>.</span></span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">When <em>d</em> = 0.200 mm, <em>s</em> = 0.9 mm and <em>D</em> = 280 mm, determine the percentage uncertainty in the wavelength.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Explain how the student could use this apparatus to obtain a more reliable value for λ. </span></p>
<div class="marks">[2]</div>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;">Evidence of&nbsp;<span style="background-color:#ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\frac{{\Delta s}}{s}{\text{AND}}\frac{{\Delta D}}{D}">
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>s</mi>
    </mrow>
    <mi>s</mi>
  </mfrac>
  <mrow>
    <mtext>AND</mtext>
  </mrow>
  <mfrac>
    <mrow>
      <mi mathvariant="normal">Δ</mi>
      <mi>D</mi>
    </mrow>
    <mi>D</mi>
  </mfrac>
</math></span> used &nbsp;&nbsp;<span style="display:inline !important;float:none;background-color:#ffffff;color:#000000;font-family:Verdana , Arial , Helvetica , sans-serif;font-size:14px;font-style:normal;font-variant:normal;font-weight:400;letter-spacing:normal;text-align:left;text-decoration:none;text-indent:0px;white-space:normal;">✔</span></span><span style="background-color:#ffffff;"><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><span style="background-color:#ffffff;">«add fractional/% uncertainties»<br></span></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><span style="background-color:#ffffff;">obtains 11 % (or 0.11) <em><strong>OR</strong> </em>10 % (or 0.1) ✔</span></span></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>ALTERNATIVE 1:</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">measure the combined width for several fringes<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">repeat measurements ✓<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">take the average<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">so the «percentage» uncertainties are reduced ✓<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>ALTERNATIVE 2:</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">increase <em>D</em> «hence <em>s</em>»<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">Decrease <em>d</em> ✓<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">so the «percentage» uncertainties are reduced ✓</span></p>
<p style="text-align:left;"><em><span style="background-color:#ffffff;"><span style="background-color:#ffffff;">Do not accept answers which suggest using different apparatus.</span></span></em></p>
<div class="question_part_label">b.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>A very easy question about percentage uncertainty which most candidates got completely correct. Many candidates gave the uncertainty to 4 significant figures or more. The process used to obtain the final answer was often difficult to follow.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>The most common correct answer was the readings should be repeated and an average taken. Another common answer was that D could be increased to reduce uncertainties in s. The best candidates knew that it was good practice to measure many fringe spacings and find the mean value. Quite a few candidates incorrectly stated that different apparatus should be used to give more precise results.</p>
<div class="question_part_label">b.</div>
</div>
<br><hr><br><div class="specification">
<p><span style="background-color: #ffffff;">An experiment is conducted to determine how the fundamental frequency <em>f</em> of a vibrating wire varies with the tension <em>T</em> in the wire.<br></span></p>
<p><span style="background-color: #ffffff;">The data are shown in the graph, the uncertainty in the tension is not shown.</span></p>
<p><span style="background-color: #ffffff;"><img 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"></span></p>
</div>

<div class="specification">
<p><span style="background-color: #ffffff;">It is proposed that the frequency of oscillation is given by<em> f</em><sup>2</sup> = <em>kT</em> where <em>k</em> is a constant.</span></p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Draw the line of best fit for the data.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Determine the fundamental SI unit for <em>k</em>.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">bi.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Write down a pair of quantities that, when plotted, enable the relationship <em>f</em><sup>2</sup> = <em>kT </em>to be verified.</span></p>
<div class="marks">[1]</div>
<div class="question_part_label">bii.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p><span style="background-color:#ffffff;">Describe the key features of the graph in (b)(ii) if it is to support this relationship.</span></p>
<div class="marks">[2]</div>
<div class="question_part_label">biii.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">Any curve that passes through ALL the error bars ✔<br></span></p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">kg<sup>–1</sup> m<sup>–1</sup> ✔<br></span><span style="background-color:#ffffff;"><br></span></p>
<div class="question_part_label">bi.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;"><em>f</em><sup>2</sup> AND <em>T</em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em>f</em> AND&nbsp;<span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="\sqrt T ">
  <msqrt>
    <mi>T</mi>
  </msqrt>
</math></span><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">log<em> f</em> AND log <em>T</em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;"><em><strong>OR</strong></em><br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">ln<em> f</em> AND ln <em>T</em> ✔</span><span style="background-color:#ffffff;"><br></span><span style="background-color:#ffffff;"><br></span></p>
<div class="question_part_label">bii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p style="text-align:left;"><span style="background-color:#ffffff;">graph would be a straight line/constant gradient/linear ✔<br></span></p>
<p style="text-align:left;"><span style="background-color:#ffffff;">passing through the origin ✔</span><span style="background-color:#ffffff;"><br></span></p>
<div class="question_part_label">biii.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Most candidates correctly drew curves which passed through all the error bars, some tried to draw straight lines. Quite a few did not draw any line, leaving the question unanswered. Candidates need to make sure to check that they read the question paper carefully.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Determining the fundamental units of K (kg-1 m-1 ) was difficult for most candidates.</p>
<div class="question_part_label">bi.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>These questions were not well understood, but a few candidates were able to state that a plot of f2 versus T would give a straight line through the origin.</p>
<div class="question_part_label">bii.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>These questions were not well understood, but a few candidates were able to state that a plot of f2 versus T would give a straight line through the origin.</p>
<div class="question_part_label">biii.</div>
</div>
<br><hr><br><div class="specification">
<p>In an investigation a student folds paper into cylinders of the same diameter <em>D</em> but different heights. Beginning with the shortest cylinder they applied the same fixed load to each of the cylinders one by one. They recorded the height <em>H</em> of the first cylinder to collapse.</p>
<p style="text-align: center;"><img 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uyH8qXM0spXG7T7i/+h/esXKz/zxqjrglo35+vGrnVD1tqh66IUnD17iMUrfsQvFoq0gQACCNhS4BN59z2l8iNztP/cVhVPHhdSsBajvi8pfcAqyZOmamaadKqvPdLSNXXSOOlcXxsM9/1xmjQ1XWlq7rOhK88g9Llpjw+SBjq2th679Xzh82rf8sd1ZN5+nXupWJPDpxXa6+U63SrN7Ll59FdOzZw6MXg2KCVDecXWv4e1ydeqpoM/07NL85XreV1n1lh7p6lgR70Ol03vefYoesMxfTc8tJg2SmMIIIAAAnYQ6NA5z/tS1hc0Iy1clFgXvfxfXfzwb70APrpyKqSjRZ7TTpUU3qbU1NtUWOLU6RN/iLh6xGoi3Ee6pqRcE5yS6NVybF4mKTXnLpWk/VEn3vv3iPUaVghWnL2narp7TUr/khZecdbiE3ndC+RwLJC77b8NYGz9fB2HY+g1Hea7dFGR1ycFo3pfnnPd1wNZVyF1nGvW6bQCFeZM6A48/CwpTdnFD6m0JFut1lmhlL5ycVFNlV+Vo9A9out9+pEIR81fBBBAAAEEegtMUE5hgdLq9mpnw/ngl7mvVSer1mmp+73eG6t18yY9XXMmdGXIe3IvW67qeRV6NNe6amaCZn1rmb58+ElVVJ0IFSfWVTIuLdo8SVs2FisjSQoWAS2q3vWazgTWnLTLW7NV663Lg7seoXUpgdefqKPjP7s+6X4SWncReMOnjzo+ki81R9/aMEuHl65T1cnW4Hisqaply7U5c5U2LsiIfvYgaZrmuZYoc/MmPVMfdPC1/lY7q99S7paVWpAxeUBj644tyrNQ4VZXvVcNrcEpLV/rCVVVPCn3FfNPTdq8fqtqApdZB68IWrboVc3bvkS5qUkK3lG2UK5wLqzCxfsb1Z6UypbkKz1ponIfrdC8Xrnw1mzWylXqykWUKGPyFoVJTBhpBAEEELCjQJJSc5fp1Z0z9bv8KUq21iNM+a5+c0upDu5frbQeJNerYMvDynv/B8qwthv/gI5lVaqhqig0LWFdyVKiHzdUaU7bU3ImW2saput/ee7Ubs8ercy+KdhaUoYWbHtZK1SpW8cny+G4XzsuFeiJn9wf0du1Sp/3sB6/vFaZydN0377mnmdAQlsmpRfK9fhfVZ55g2647xdq9llXnvxIDbvnqM2VHRzP+H+RZ06VPK8uV3ZKX1+Z1lUtj2tP4yJ1rr8jsF+ys1KdD+3RnhWzQlfpDGBsESO48ulE5f7zc9o56w3lOz8VuI/JlO/+TreUPqf91qXRPR4FWl1yq95/+k45HMkan1evrF37VVX82UBhlZSxSDsbl+jmQ/drfGANSbLG5x7Szcte1Iai0DaTi1TVIxc3KvfQBC1rfEkrwrno0WfsXjj81kXnPBBAAAEERkXA4XDowIEDo9JXf53Mnz8/cN+R/rbj83gRCN84rlkbPD8NXfobL7F3x9lX+de9Bc8QQAABBBBAAIFREqAwGSVoukEAAQQQQACB/gW4XLh/I7ZAAAEEEEAgDgRCN7yL8wUanDGJg0ONEBFAAAEEELCLAIWJXTLNOBFAAAEEEIgDAa7KiYMkESICCJgjYF1Vw6NbgAs7uy14FhsBzpjExpFWEEDAJgLWF/Fw/llMw9k/lvsOJ5a//MX6XRyprq4u8Jf/QCBWAhQmsZKkHQQQQMBGAs8880xgtGvXrtXHH39so5Ez1JEWYCpnpIVpHwEEEIgQsKaCrLMeJjyGGovX61VmZmbXEHbt2qVvfvObXa95gsBwBChMhqPHvggggMAgBYZaDAyymwFtPtRYioqKdOjQoR59WFM7EyZE+YG4HlvxAoH+BZjK6d+ILRBAAAEEQgLWmpLeRYn1UXhqBygEhivAGZPhCrI/AgggMAiBoZ6lGEQXA950sLFYa0nmzJmjN998M2ofb7/9tmbOnBn1M95EYKACFCYDlWI7BBBAIAYCgy0GYtBln00MNharMPnggw+62rPWmXg8nq7XEydOZDqnS4MnQxWgMBmqHPshgAACQxAYbDEwhC4GvMtwYxnu/gMOlA1tJcAaE1ulm8EigAACCCBgtgCFidn5IToEEEAAAQRsJUBhYqt0M1gEEEAAAQTMFrjG7PCIDgEEhiJgzf2b8jDlZmKmeBAHAghcXYDC5Oo+fIpA3AocOHBgzGOfP3/+mMdAAAggEF8CTOXEV76IFgEEEEAAgYQWoDBJ6PQyOAQQQAABBOJLgMIkvvJFtAgggAACCCS0AIVJQqeXwSGAAAIIIBBfAhQm8ZUvokUAAQQQQCChBShMEjq9DA4BBBBAAIH4EqAwia98ES0CCCCAAAIJLUBhktDpZXAIIIAAAgjElwCFSXzli2gRQAABBBBIaAEKk4ROL4NDAAEEEEAgvgQoTOIrX0SLAAIIIIBAQgtQmCR0ehkcAggggAAC8SVAYRJf+SJaBBBAAAEEElqAwiSh08vgEEAAAQQQiC8BCpP4yhfRIoAAAgggkNACFCYJnV4GhwACCCCAQHwJUJjEV76IFgEEEEAAgYQWoDBJ6PQyOAQQQAABBOJLgMIkvvJFtAgggAACCCS0AIVJQqeXwSGAAAIIIBBfAhQm8ZUvokUAAQQQQCChBShMEjq9DA4BBBBAAIH4EqAwia98ES0CCCCAAAIJLUBhktDpZXAIIIAAAgjElwCFSXzli2gRQAABBBBIaAEKk4ROL4NDAAEEEEAgvgQoTOIrX0SLAAIIIIBAQgtQmCR0ehkcAggggAAC8SVAYRJf+SJaBBBAAAEEElqAwiSh08vgEEAAAQQQiC8BCpP4yhfRIoAAAgggkNACFCYJnV4GhwACCCCAQHwJOPx+vz++QiZaBBJbwOFwJPYABzm6RPufKCu/poxpuLEMd/9BHgpsbhOBa2wyToaJQNwIxOJLy5QvDFPiiJvkEygCCIipHA4CBBBAAAEEEDBGgMLEmFQQCAIIIIAAAghQmHAMIIAAAggggIAxAhQmxqSCQBBAAAEEEECAwoRjAAEEEEAAAQSMEaAwMSYVBIIAAggggAACFCYcAwgggAACCCBgjAD3MTEmFfEViHV/ClMesbjvhyljIQ4EEEDA7gIUJnY/AoYx/gMHDgxj79jsOn/+/Ng0RCsIIIAAAkYIMJVjRBoIAgEEEEAAAQQsAQoTjgMEEEAAAQQQMEaAwsSYVBAIAggggAACCFCYcAwggAACCCCAgDECFCbGpIJAEEAAAQQQQIDChGMAAQQQQAABBIwRoDAxJhUEggACCCCAAAIUJhwDCCCAAAIIIGCMAIWJMakgEAQQQAABBBCgMOEYQAABBBBAAAFjBChMjEkFgSCAAAIIIIAAhQnHAAIIIIAAAggYI0BhYkwqCAQBBBBAAAEEKEw4BhBAAAEEEEDAGAEKE2NSQSAIIIAAAgggQGHCMYAAAggggAACxghQmBiTCgJBAAEEEEAAgREoTNrlranQXIdDDodThT/Zp58UOuV01at9pL3b6+VyOlXoPiNf1L4+kde9QI5Ct7zRN4i619Df9Km9vkJOxwK5vZ8MvRn2RAABBBBAwCYC18R6nD7vL7Xsvlc1bf9ZvV78WQUqn8ULtDjWHdEeAggggAACCCScwAicMbGMPqWJN90QLEoSjowBIYAAAggggMBICcSwMAlOkyRnlqtOTdqcf7MczgrV/8cf5O6ayrmopsqvyuFcqprzl0Nj8qmj6Uea68hSec2fQlMwl9XaVC3XXKccgSmhQrnc9fJ2RM6/WNvUqLI0K7iNs1SVh99S26Cl2uWtdw+uLyumuS65673qiOzP16qmmkqVOq1pLIecpVt1+K3zkVvwHAEEEEAAAQSuIhDDwuRaZZTtU6dnhwqUrdWv/1n+lo3KuzGyi5uU/e112pJZo6XrfqXzVp3R0agXVm6Rp+z7eqrImvq5rPM1K5R9z1FN2tSkTr9f/ks/VOax5cpdfjC4j6xi5sd6MOdF/fneV3TJ2sb7uKa9dUQ/bb3KaK/4qF1n3I8pd9Gxrr46W9Zp0rHlyrynSk2BQijU1z2HlPxIXTAe/9/U8sT1qs5foReaLoZavaimrQ8rZ9sF3dvwV/n9nfKumaa3XjuiQYV0RYy8gQACCCCAgH0EIquG0Rl1So6+XblKme4nte7g2zr5wlNa5SnW9qe+qslWNO3H9ezSGmVteFzLZ6UFp4NSZqhsW5VKDm/Usw0fSrqgk/t+Js9ql9YUT1eKFXnKdBWvcWl12iCG0d6ol9ee1LztT3X1lZR2px7bVqXVni2q2OeVL9xXSanKw/FonNJyF6qk4IyOvNMWPMvT/pb2bW3T6idWqDgjVVKSUjKKtOaJhzSYkAYRPZsigAACCCCQcAKjX5hYX9jZ31Llls/Kfd8X9MVV0pZXN6h48jhJPrU3HlV1q1Mzp07suUYlxanMrBZV176r9vZ3VVvdoqxMZ7AoCaclsM314Vf9/A33davunPF3UfqSTnta1KGJytvUqJZNOWqrP6SamhrV1LwkV36eyus+CvURbmuaMqcEyqTQ+0lKmZKurH4i4WMEEEAAAQQQCAqMQWFidXyTbn+gTGXWqYTcfM3NtM4wRD5Ca1QC60uC6zUcybeqvC44KdLZdlanhj0/clltZ5uvOs3Seuqs2nw+dZzZpVLnjcrMf06/v2jNP31Ghc/XaEdBuHjpv63I0fEcAQQQQAABBKILjE1h4vuTDq57Uu7/mqtczxatfKGx5yJS3a8dno/lt9aO9PrXsilP/2XSVM0c9vzIOE2amn7VaZa0mVM1SV7tW/64jszbr3OdtdpU9k8qLr5Xec6P5Dkdro76bys6P+8igAACCCCAQKTAGBQml3X+4BYtdX9WW57dq93bi+VZ9VRoEWmSUnPuUknaH3XivX/veZO0jpOqnJsevHla6m0qLHGGploihtPRIs/p8PRKxPtRn16tL6sdBaeKAm1KWXd+TmkRWr5LF2Wtdgk+wm29L8+5yOt0fOo416zT4c34iwACCCCAAAJXFYj4qr3qdjH70Hf+V1q3tEaZW9bp29mf0eSiVdpe9ietWvly8CqY1Nl6dPscHV66TlUnW4PFSccZ1ax/Qqv0iDYuyFCSJir30QrNq16uZe73gmdbrG2e3qTN4ZMYA4k4NUff2jCrV1/vyb1suTZnrgr2FSqC6qr3qqE1eImzr/WEqiqelDuyr0Dc/6DqRS65z1j3uPWpw3tQT6/fedXpooGEyTYIIIAAAgjYRWB0C5PwFE7mKlV+Oye4cDXpsyp66vsq65rSGafJxRvVsHuO2lzZSrbWmYy/X4duXqLGPY8oOyUYctLkIlU1VCrr2AMaH9hmuX5/R5m2FAx08auV4lRNL/tRr77+RZ45VfK8ujzU10Tl/vNz2jnrDeU7PxW4P8mU7/5Ot5Q+p/2rsyOOk1Dcu2boWN6NcjiSNX5Jo+5Y9qgKIrbiKQIIIIAAAgj0LeDwW4s4eCAwSAHrBnIHDhwY5F6x33z+/PmBdUixbzm+W7TyY8J/tU2Jw6RsmmQy3FiGu79JeSEWcwRG94yJOeMmEgQQQAABBBAwUIDCxMCkEBICCCCAAAJ2FWAqx4aZt06/8ugWMGHKozua2Dwz5RS7KXHERjU2rZhkMtxYhrt/bERpJdEErkm0ATGe/gVi8UVsyv8gmRJH/+psgQACCCAwEAGmcgaixDYIIIAAAgggMCoCFCajwkwnCCCAAAI+r1uFjhy56rtvTxmp0t/nkdvyPHEFjJ3KsU7Rm/KIxdSHKWMhDgQQQGBsBMJ3wp6mhT1+7DQczSdqPv5vqksrkCtnQvhN/tpQwNjCxMqFKffJsOFxwZARQACBGAuEfuw0LV1TJ1m/Jt/70aFznvelrLs1JXQjzd5b8NoeAkzl2CPPjBIBBBAYWwHfWR3fe1xpJXcpJzXKV4/vQ5091aLAj6dG+Xhsg6f30RQg/aOpTV8IIICAXQXCP4ia6Qz+HElvh/4+7709rxNWwOipnIRVZ2AIIICAzQR8bWd1qrVVdeW3Krm8r6n6V1wAAAy/SURBVMHfrx2zp4r/x9yXjz3eJ//2yDOjRAABBMZQILzw9X7t8Hwc+B0n66KC7n8fy7PjfqnP9SdjGDpdj7oAhcmok9MhAgggYDeBC2qsrVNrwd2anX5tlMGHF76ms/A1io7d3qIwsVvGGS8CCCAw2gL9LWzt7/PRjpf+xlSAwmRM+ekcAQQQsIFAPwtbfc1vaG+dUyWFtynVBhwM8eoCFCZX9+FTBBBAAIFhCfjU3nhU1a2ztTDqwtbw+pNpyox647Vhdc7OcShAYRKHSSNkBBBAIH4E+ruxWn+fx89IiTQ2Ag6/ofdbt25Jb8qdXw0lis0RMMRWTPlVX1PiGCLjiO1miospcYwY9BAaNslkuLEMd/8h8LGLDQQ4Y2KDJDNEBBBAAAEE4kWAwiReMkWcCCCAAAII2ECAwsQGSWaICCCAAAIIxIsAhUm8ZIo4EUAAAQQQsIEAhYkNkswQEUAAAQQQiBcBCpN4yRRxIoAAAgggYAMBChMbJJkhIoAAAgggEC8CFCbxkiniRAABBBBAwAYCFCY2SDJDRAABBBBAIF4EKEziJVPEiQACCCCAgA0EKExskGSGiAACCCCAQLwIUJjES6aIEwEEEEAAARsIUJjYIMkMEQEEEEAAgXgRoDCJl0wRJwIIIIAAAjYQoDCxQZIZIgIIIIAAAvEiQGESL5kiTgQQQAABBGwgQGFigyQzRAQQQAABBOJFgMIkXjJFnAgggAACCNhAgMLEBklmiAgggAACCMSLAIVJvGSKOBFAAAEEELCBAIWJDZLMEBFAAAEEEIgXAQqTeMkUcSKAAAIIIGADAYff7/fHepwOhyPWTcZ1eyNAPOYeVo5NGJcpcYx5QnoFYIqLKXH04hnTlyaZDDeW4e4/pomgc2MFrhmJyGLxhWXKAW9KHCORJ9pEAAEEEEDANAGmckzLCPEggAACCCBgYwEKExsnn6EjgAACCCBgmgCFiWkZIR4EEEAAAQRsLEBhYuPkM3QEEEAAAQRME6AwMS0jxIMAAggggICNBShMbJx8ho4AAggggIBpAhQmpmWEeBBAAAEEELCxAIWJjZPP0BFAAAEEEDBNgMLEtIwQDwIIIIAAAjYWoDCxcfIZOgIIIIAAAqYJUJiYlhHiQQABBBBAwMYCFCY2Tj5DRwABBBBAwDQBChPTMkI8CCCAAAII2FiAwsTGyWfoCCCAAAIImCZAYWJaRogHAQQQQAABGwtQmNg4+QwdAQQQQAAB0wQoTEzLCPEggAACCCBgYwEKExsnn6EjgAACCCBgmgCFiWkZIR4EEEAAAQRsLEBhYuPkM3QEEEAAAQRME6AwMS0jxIMAAggggICNBShMbJx8ho4AAggggIBpAhQmpmWEeBBAAAEEELCxAIWJjZPP0BFAAAEEEDBNgMLEtIwQDwIIIIAAAjYWoDCxcfIZOgIIIIAAAqYJUJiYlhHiQQABBBBAwMYCFCY2Tj5DRwABBBBAwDQBChPTMkI8CCCAAAII2FiAwsTGyWfoCCCAAAIImCZAYWJaRogHAQQQQAABGwtQmNg4+QwdAQQQQAAB0wQoTEzLCPEggAACCCBgYwEKExsnn6EjgAACCCBgmgCFiWkZIR4EEEAAAQRsLEBhYuPkM3QEEEAAAQRME6AwMS0jxIMAAggggICNBShMbJx8ho4AAggggIBpAhQmpmWEeBBAAAEEELCxAIWJjZPP0BFAAAEEEDBNgMLEtIwQDwIIIIAAAjYWoDCxcfIZOgIIIIAAAqYJUJiYlhHiQQABBBBAwMYCFCY2Tj5DRwABBBBAwDQBChPTMkI8CCCAAAII2FiAwsTGyWfoCCCAAAIImCZAYWJaRogHAQQQQAABGwtQmNg4+QwdAQQQQAAB0wQoTEzLCPEggAACCCBgYwEKExsnn6EjgAACCCBgmgCFiWkZIR4EEEAAAQRsLEBhYuPkM3QEEEAAAQRME6AwMS0jxIMAAggggICNBShMbJx8ho4AAggggIBpAhQmpmWEeBBAAAEEELCxAIWJjZPP0BFAAAEEEDBNgMLEtIwQDwIIIIAAAjYWoDCxcfIZOgIIIIAAAqYJUJiYlhHiQQABBBBAwMYCFCY2Tj5DRwABBBBAwDQBChPTMkI8CCCAAAII2FiAwsTGyWfoCCCAAAIImCZAYWJaRogHAQQQQAABGwtQmNg4+QwdAQQQQAAB0wQoTEzLCPEggAACCCBgYwEKExsnn6EjgAACCCBgmgCFiWkZIR4EEEAAAQRsLEBhYuPkM3QEEEAAAQRME6AwMS0jxIMAAggggICNBShMbJx8ho4AAggggIBpAhQmpmWEeBBAAAEEELCxAIWJjZPP0BFAAAEEEDBN4BrTAiIeBBBAAAEzBS5cuKCGhoYewdXU1HS9njFjhjIyMrpe8wSBoQg4/H6/fyg7jvQ+DodDJoRmShwj7T3Y9k1xMSWOwfqN9PamuJgSx0h7D6Z9k0yGEktRUZEOHToUdcgffPCBpkyZEvUz3kRgoAJM5QxUiu0QQAABBPS9730vqsK2bdsoSqLK8OZgBShMBivG9ggggICNBWbOnKlVq1b1ELjjjjtUXl7e4z1eIDBUAaZy+pEbyqnOfppMiI9NcTElDtOSaoqLKXGYlB+TTIYai7XW5NOf/nQXa21trQoKCrpe8wSB4QhwxmQ4euyLAAII2FBgwoQJ2rVrV2Dk9957L0WJDY+BkRwyZ0z60R3q/6Pop9m4/9gUF1PiMC2hpriYEodJ+THJZDixfPzxx5ozZ452797NlTgmHWAJEItDkpFX5SSALUNAAAEEEDBUwISrPg2lGfOwriE5Y54DAkAAAQQQQACBkEDcrTGxFl3F+mGdkuSBAAIIIIAAAmMvEDeFiVU8WHcYvPvuu2OudvjwYa1evVrnzp2Leds0iAACCCCAAAIDF4iLwuTUqVN64IEHdN999+nNN98c+OgGseWWLVt0yy236Kc//ak4gzIIODZFAAEEEEAghgJGFybWGQzrTMbtt9/e5y2QY2gRaKq0tDSw0ryuri7WTdMeAggggAACCPQjYOzlwtu3b9eyZcv6CX9kP7auz7fi4LcfRtaZ1hFAAAEEEAgLGHvGxPqhqN63PQ4HbV1JFMt/+/fvDzfd9de6xfJ3vvMdipIuEZ4ggAACCCAw8gLGFibWWYrNmzfr7bfflnXmYjQf1o9RHTt2jLsZjiY6fSGAAAIIICDJ2MIknB3rB6N+/vOfyzqrYZ3FGMmHdYbG+tnupUuX6rrrrhvJrmgbAQQQQAABBKIIGLvGJEqssu5hsmfPnkDhEO3zob534sQJ3XDDDbKKIB4IIIAAAgggMHYCcVWYjB0TPSOAAAIIIIDAaAgYP5UzGgj0gQACCCCAAAJmCFCYmJEHokAAAQQQQACBeFj8OrgsfSKve4Gsn/Lu+a9QLne9vB2+wTXH1ggggAACCCAwqgKJdcbEd1bH9x6XCnbI0xlxr5NL23TXhV3KvadKTRQno3qA0RkCCCCAAAKDEUiswqSjRZ7TUsHCLyk9cmQpGfryise1YdyPVbHPK86bDOYQYVsEEEAAAQRGTyDy63v0eh2Rnnxqbzyq6lanZk6deOUNWpKmavbCL6hu7xtqpjIZkQzQKAIIIIAAAsMVSKDC5LLazjarNa1AhTkT+nY53axzTOf07cMnCCCAAAIIjKFA4hQm4fUlWemakpI4wxrDY4OuEUAAAQQQGHWBxPkG72t9SRdph8553pcoXLpEeIIAAggggIBpAglSmPSzvsRS932os6cuXrkw1rSMEA8CCCCAAAI2FkiQwqS/9SU+dbx9WNWn79aSwmlXLoy18QHA0BFAAAEEEDBJIDEKk/7Wl3Q06oWVP9O07atUNHmcSf7EggACCCCAAAIRAolRmPS5vsSnDm+tKh9x6XTJTlUVf5azJRHJ5ykCCCCAAAKmCSTArwv71F6/VtPzf6DWK3Rn6Jtb1qr0a/OUl5F6xae8gQACCCCAAAJmCSRAYWIWKNEggAACCCCAwNAFEmMqZ+jjZ08EEEAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEiAwsSgZBAKAggggAACdhegMLH7EcD4EUAAAQQQMEjg/wPD+rw1nRVEEwAAAABJRU5ErkJggg=="></p>
<p style="text-align: left;">They then repeat this process with cylinders of different diameters.</p>
<p style="text-align: left;">The graph shows the data plotted by the student and the line of best fit.</p>
<p style="text-align: center;"><img src="data:image/png;base64,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"></p>
<p style="text-align: left;">Theory predicts that <em>H</em> = <span style="background-color: #ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="c{D^{\frac{2}{3}}}">
  <mi>c</mi>
  <mrow>
    <msup>
      <mi>D</mi>
      <mrow>
        <mfrac>
          <mn>2</mn>
          <mn>3</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span> </span>where <em>c</em> is a constant.</p>
</div>

<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Suggest why the student’s data supports the theoretical prediction.</p>
<div class="marks">[2]</div>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Determine <em>c</em>. State an appropriate unit for <em>c</em>.</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Determine <em>c</em>. State an appropriate unit for <em>c</em>.</p>
<div class="marks">[3]</div>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px; padding-right: 20px;">
<p>Identify <strong>one</strong> factor that determines the value of <em>c</em>.</p>
<div class="marks">[1]</div>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Markscheme</h2>
<div class="question" style="padding-left: 20px;">
<p>theory «<span style="background-color:#ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="H = c{D^{\left( {\frac{2}{3}} \right)}}">
  <mi>H</mi>
  <mo>=</mo>
  <mi>c</mi>
  <mrow>
    <msup>
      <mi>D</mi>
      <mrow>
        <mrow>
          <mo>(</mo>
          <mrow>
            <mfrac>
              <mn>2</mn>
              <mn>3</mn>
            </mfrac>
          </mrow>
          <mo>)</mo>
        </mrow>
      </mrow>
    </msup>
  </mrow>
</math></span></span>» predicts that <em>H</em><sup>3</sup> ∝ <em>D</em><sup>2&nbsp;</sup>✔</p>
<p>graph «of <em>H</em><sup>3</sup> vs <em>D</em><sup>2</sup> » is a straight line through&nbsp;the origin/graph of proportionality ✔</p>
<p><em>Allow <span style="display:inline !important;float:none;background-color:#ffffff;color:#000000;font-family:Verdana , Arial , Helvetica , sans-serif;font-size:14px;font-style:normal;font-variant:normal;font-weight:400;letter-spacing:normal;text-align:left;text-decoration:none;text-indent:0px;white-space:normal;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="H = c{D^{\left( {\frac{2}{3}} \right)}}">
  <mi>H</mi>
  <mo>=</mo>
  <mi>c</mi>
  <mrow>
    <msup>
      <mi>D</mi>
      <mrow>
        <mrow>
          <mo>(</mo>
          <mrow>
            <mfrac>
              <mn>2</mn>
              <mn>3</mn>
            </mfrac>
          </mrow>
          <mo>)</mo>
        </mrow>
      </mrow>
    </msup>
  </mrow>
</math></span></span> gives H<sup>3</sup> = c<sup>3</sup>D<sup>2</sup> for MP1.</em></p>
<p><em>Do not award MP2 for “the graph is linear” without mention of origin</em>.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>evidence of gradient calculation to give gradient = 3.0 ✔</p>
<p><em>c</em><sup>3</sup> = 3.0 ⇒ <em>c =&nbsp;</em>1.4 ✔</p>
<p><span style="background-color:#ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{m^{\frac{1}{3}}}">
  <mrow>
    <msup>
      <mi>m</mi>
      <mrow>
        <mfrac>
          <mn>1</mn>
          <mn>3</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span></span></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>evidence of gradient calculation to give gradient = 3.0 ✔</p>
<p><em>c</em><sup>3</sup> = 3.0 ⇒ <em>c =&nbsp;</em>1.4 ✔</p>
<p><span style="background-color:#ffffff;"><span class="mjpage"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{m^{\frac{1}{3}}}">
  <mrow>
    <msup>
      <mi>m</mi>
      <mrow>
        <mfrac>
          <mn>1</mn>
          <mn>3</mn>
        </mfrac>
      </mrow>
    </msup>
  </mrow>
</math></span></span></p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>the load/the thickness of paper/the type of paper/ the number of times the paper is rolled to form a cylinder ✔</p>
<div class="question_part_label">c.</div>
</div>
<h2 style="margin-top: 1em">Examiners report</h2>
<div class="question" style="padding-left: 20px;">
<p>Load on a cylinder. The question was successful for candidates well prepared to write conclusions in their lab reports. Theory in the stem of the question predicts a directly proportional relationship between <em>H</em> and <em>D</em><sup>2/3</sup>, which graphed are <em>H</em><sup>3</sup> and <em>D</em><sup>2</sup>. Well prepared candidates were able to identify, that the theory predicts that <em>H</em><sup>3</sup> should be directly proportional to <em>D</em><sup>2</sup> and that this proportionality can be seen from the graph. Many candidates were able to mention that the relationship was linear and passed through the origin (as an alternative to proportional). However, a common response mentioned only linear or linear regression which is not sufficient to fully demonstrate proportionality.</p>
<div class="question_part_label">a.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Part b) was the most difficult part of section A, but still accessible. Many candidates only calculated the slope of the graph and did not realise that the third root of the slope is the constant c. Some students who were able to achieve the numerical value of c=1.4 struggled to establish the correct unit - perhaps lacking confidence or familiarity with the notion that a unit could be raised to a fractional index.</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>Part b) was the most difficult part of section A, but still accessible. Many candidates only calculated the slope of the graph and did not realise that the third root of the slope is the constant c. Some students who were able to achieve the numerical value of c=1.4 struggled to establish the correct unit - perhaps lacking confidence or familiarity with the notion that a unit could be raised to a fractional index.</p>
<div class="question_part_label">b.</div>
</div>
<div class="question" style="padding-left: 20px;">
<p>In c) most of the candidates well identified the load or the type of the paper as possible controlled variables. A common mistake here was answer discussing the height or the diameter of the cylinders.</p>
<div class="question_part_label">c.</div>
</div>
<br><hr><br>