Edexcel Paper 3 2023 June — Question 6 14 marks

Exam BoardEdexcel
ModulePaper 3 (Paper 3)
Year2023
SessionJune
Marks14
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicData representation
TypeEstimate percentages or proportions from graphs
DifficultyModerate -0.3 This is a multi-part question covering standard A-level statistics content: reading histograms, evaluating model suitability, integration by parts (a routine technique), and applying models. Part (c) is a standard integration by parts exercise, parts (a) and (e) involve straightforward calculations, and parts (b) and (f) require basic interpretation. While lengthy with multiple parts, each component uses familiar techniques without requiring novel insight.
Spec1.08i Integration by parts2.02b Histogram: area represents frequency2.04e Normal distribution: as model N(mu, sigma^2)2.04f Find normal probabilities: Z transformation

  1. A medical researcher is studying the number of hours, \(T\), a patient stays in hospital following a particular operation.
The histogram on the page opposite summarises the results for a random sample of 90 patients.
  1. Use the histogram to estimate \(\mathrm { P } ( 10 < T < 30 )\) For these 90 patients the time spent in hospital following the operation had
    • a mean of 14.9 hours
    • a standard deviation of 9.3 hours
    Tomas suggests that \(T\) can be modelled by \(\mathrm { N } \left( 14.9,9.3 ^ { 2 } \right)\)
  2. With reference to the histogram, state, giving a reason, whether or not Tomas' model could be suitable. Xiang suggests that the frequency polygon based on this histogram could be modelled by a curve with equation $$y = k x \mathrm { e } ^ { - x } \quad 0 \leqslant x \leqslant 4$$ where
    • \(x\) is measured in tens of hours
    • \(k\) is a constant
    • Use algebraic integration to show that
    $$\int _ { 0 } ^ { n } x \mathrm { e } ^ { - x } \mathrm {~d} x = 1 - ( n + 1 ) \mathrm { e } ^ { - n }$$
  3. Show that, for Xiang's model, \(k = 99\) to the nearest integer.
  4. Estimate \(\mathrm { P } ( 10 < T < 30 )\) using
    1. Tomas' model of \(T \sim \mathrm {~N} \left( 14.9,9.3 ^ { 2 } \right)\)
    2. Xiang's curve with equation \(y = 99 x \mathrm { e } ^ { - x }\) and the answer to part (c) The researcher decides to use Xiang's curve to model \(\mathrm { P } ( a < T < b )\)
  5. State one limitation of Xiang's model. \begin{figure}[h]
    \captionsetup{labelformat=empty} \caption{Question 6 continued} \includegraphics[alt={},max width=\textwidth]{a067577e-e2a6-440b-9d22-d558fade15f0-17_1164_1778_294_146}
    \end{figure} Time in hours

Question 6:
Part (a)
AnswerMarks Guidance
Answer/WorkingMark Guidance
\(2\times4.2, 4\times4, 4\times3.5, 10\times1\) \((= 8.4+16+14+10 = 48.4)\)M1 Attempt to find number between 10 and 30; 2 correct products or 48 or 48.4 seen
\(\left[\frac{48.4}{90}\right] = \frac{121}{225} = 0.53777...\) 0.53~0.54 (2sf OK)A1 For 2sf answer in \([0.53 \sim 0.54]\); NB use of 48 gives 0.5333...
Part (b)
AnswerMarks Guidance
Answer/WorkingMark Guidance
Data is not symmetric or is skew (normal is symmetric); "Even" distribution or diagram alone not sufficientB1 Comment suggesting not suitable based on lack of symmetry or "not bell shaped"
Part (c)
AnswerMarks Guidance
Answer/WorkingMark Guidance
\(\int xe^{-x}\,dx = \int x\,d(-e^{-x})\)M1 Attempting integration by parts in right direction; must have \(u=x\) and \(v=\pm e^{-x}\)
\(= \left[-xe^{-x}\right] - \int(-e^{-x})\,dx \quad (+c)\)A1 Correct first step and expression for second integral
\(\int_0^n xe^{-x}\,dx = \left[-xe^{-x}-e^{-x}\right]_0^n = \left(-ne^{-n}-e^{-n}\right)-\left[-(0)-1\right]\)dM1 Dep on 1st M1; all integration attempted and some use of at least one limit
\(= 1-(n+1)e^{-n}\) (*)A1cso* cso with no incorrect working; minimum is correct integration and use of limits
Part (d)
AnswerMarks Guidance
Answer/WorkingMark Guidance
Require area \(= 90\), i.e. \(k\int_0^n xe^{-x}\,dx = 90\) (ignore limits)M1 Realising need area under curve (implied by integral) \(= 90\)
Using result in (c) with \(n=4\): \(k\left[1-5e^{-4}\right]=90\)M1 Use of (c) with \(n=4\) and set \(=90\); may be implied by 99.07... or better
\((k=)\) 99(.0729...) (*)A1cso* For \(k=99\) or awrt 99.1; allow \(k=99\) with area \(=\) awrt 89.9 as conclusion for 3/3
Part (e)(i)
AnswerMarks Guidance
Answer/WorkingMark Guidance
\([P(10 < T < 30) =]\ 0.64863...\) awrt 0.649B1 For awrt 0.649
Part (e)(ii)
AnswerMarks Guidance
Answer/WorkingMark Guidance
\([\text{No. of patients}=]\ (99)\left[\left(1-4e^{-3}\right)-\left(1-2e^{-1}\right)\right]\ (=53.1..)\)M1 Use of (c) with \(n=1\) and \(n=3\); don't need the 99; implied by awrt 0.54
\(\text{Prob} = \dfrac{0.5366...\times99}{90} = 0.59027...\) awrt 0.590 or 0.591A1 Allow 0.59 from correct working
Part (f)
AnswerMarks Guidance
Answer/WorkingMark Guidance
e.g. Patients might stay longer than 40 hoursB1 Comment in context about upper limit for time (\(t\) or \(x\)); time/hour may be implied
# Question 6:

## Part (a)

| Answer/Working | Mark | Guidance |
|---|---|---|
| $2\times4.2, 4\times4, 4\times3.5, 10\times1$ $(= 8.4+16+14+10 = 48.4)$ | M1 | Attempt to find number between 10 and 30; 2 correct products or 48 or 48.4 seen |
| $\left[\frac{48.4}{90}\right] = \frac{121}{225} = 0.53777...$ **0.53~0.54** (2sf OK) | A1 | For 2sf answer in $[0.53 \sim 0.54]$; NB use of 48 gives 0.5333... |

## Part (b)

| Answer/Working | Mark | Guidance |
|---|---|---|
| Data is not symmetric or is skew (normal is symmetric); "Even" distribution or diagram alone not sufficient | B1 | Comment suggesting not suitable based on lack of symmetry or "not bell shaped" |

## Part (c)

| Answer/Working | Mark | Guidance |
|---|---|---|
| $\int xe^{-x}\,dx = \int x\,d(-e^{-x})$ | M1 | Attempting integration by parts in right direction; must have $u=x$ and $v=\pm e^{-x}$ |
| $= \left[-xe^{-x}\right] - \int(-e^{-x})\,dx \quad (+c)$ | A1 | Correct first step and expression for second integral |
| $\int_0^n xe^{-x}\,dx = \left[-xe^{-x}-e^{-x}\right]_0^n = \left(-ne^{-n}-e^{-n}\right)-\left[-(0)-1\right]$ | dM1 | Dep on 1st M1; all integration attempted and some use of at least one limit |
| $= 1-(n+1)e^{-n}$ (*) | A1cso* | cso with no incorrect working; minimum is correct integration and use of limits |

## Part (d)

| Answer/Working | Mark | Guidance |
|---|---|---|
| Require area $= 90$, i.e. $k\int_0^n xe^{-x}\,dx = 90$ (ignore limits) | M1 | Realising need area under curve (implied by integral) $= 90$ |
| Using result in (c) with $n=4$: $k\left[1-5e^{-4}\right]=90$ | M1 | Use of (c) with $n=4$ and set $=90$; may be implied by 99.07... or better |
| $(k=)$ **99**(.0729...) (*) | A1cso* | For $k=99$ or awrt 99.1; allow $k=99$ with area $=$ awrt 89.9 as conclusion for 3/3 |

## Part (e)(i)

| Answer/Working | Mark | Guidance |
|---|---|---|
| $[P(10 < T < 30) =]\ 0.64863...$ awrt **0.649** | B1 | For awrt 0.649 |

## Part (e)(ii)

| Answer/Working | Mark | Guidance |
|---|---|---|
| $[\text{No. of patients}=]\ (99)\left[\left(1-4e^{-3}\right)-\left(1-2e^{-1}\right)\right]\ (=53.1..)$ | M1 | Use of (c) with $n=1$ and $n=3$; don't need the 99; implied by awrt 0.54 |
| $\text{Prob} = \dfrac{0.5366...\times99}{90} = 0.59027...$ awrt **0.590 or 0.591** | A1 | Allow 0.59 from correct working |

## Part (f)

| Answer/Working | Mark | Guidance |
|---|---|---|
| e.g. Patients might stay longer than 40 hours | B1 | Comment in context about upper limit for time ($t$ or $x$); time/hour may be implied |
\begin{enumerate}
  \item A medical researcher is studying the number of hours, $T$, a patient stays in hospital following a particular operation.
\end{enumerate}

The histogram on the page opposite summarises the results for a random sample of 90 patients.\\
(a) Use the histogram to estimate $\mathrm { P } ( 10 < T < 30 )$

For these 90 patients the time spent in hospital following the operation had

\begin{itemize}
  \item a mean of 14.9 hours
  \item a standard deviation of 9.3 hours
\end{itemize}

Tomas suggests that $T$ can be modelled by $\mathrm { N } \left( 14.9,9.3 ^ { 2 } \right)$\\
(b) With reference to the histogram, state, giving a reason, whether or not Tomas' model could be suitable.

Xiang suggests that the frequency polygon based on this histogram could be modelled by a curve with equation

$$y = k x \mathrm { e } ^ { - x } \quad 0 \leqslant x \leqslant 4$$

where

\begin{itemize}
  \item $x$ is measured in tens of hours
  \item $k$ is a constant\\
(c) Use algebraic integration to show that
\end{itemize}

$$\int _ { 0 } ^ { n } x \mathrm { e } ^ { - x } \mathrm {~d} x = 1 - ( n + 1 ) \mathrm { e } ^ { - n }$$

(d) Show that, for Xiang's model, $k = 99$ to the nearest integer.\\
(e) Estimate $\mathrm { P } ( 10 < T < 30 )$ using\\
(i) Tomas' model of $T \sim \mathrm {~N} \left( 14.9,9.3 ^ { 2 } \right)$\\
(ii) Xiang's curve with equation $y = 99 x \mathrm { e } ^ { - x }$ and the answer to part (c)

The researcher decides to use Xiang's curve to model $\mathrm { P } ( a < T < b )$\\
(f) State one limitation of Xiang's model.

\begin{figure}[h]
\begin{center}
\captionsetup{labelformat=empty}
\caption{Question 6 continued}
  \includegraphics[alt={},max width=\textwidth]{a067577e-e2a6-440b-9d22-d558fade15f0-17_1164_1778_294_146}
\end{center}
\end{figure}

Time in hours

\hfill \mbox{\textit{Edexcel Paper 3 2023 Q6 [14]}}