AQA S3 2014 June — Question 7 4 marks

Exam BoardAQA
ModuleS3 (Statistics 3)
Year2014
SessionJune
Marks4
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicHypothesis test of a Poisson distribution
TypeOne-tailed test (increase or decrease)
DifficultyChallenging +1.2 This is a comprehensive Further Maths Statistics question covering multiple aspects of Poisson distributions. Part (a) requires standard proofs from first principles that are bookwork for S3. Part (b) involves routine hypothesis testing procedures: an exact test using tables, a normal approximation test, finding a critical value, and calculating Type II error probability. While lengthy and requiring careful execution across multiple parts, each component uses standard techniques without requiring novel insight or particularly challenging problem-solving.
Spec5.02i Poisson distribution: random events model5.02j Poisson formula: P(X=x) = e^(-lambda)*lambda^x/x!5.05a Sample mean distribution: central limit theorem5.05b Unbiased estimates: of population mean and variance5.05c Hypothesis test: normal distribution for population mean

7
  1. The random variable \(X\) has a Poisson distribution with parameter \(\lambda\).
    1. Prove, from first principles, that \(\mathrm { E } ( X ) = \lambda\).
    2. Given that \(\mathrm { E } \left( X ^ { 2 } - X \right) = \lambda ^ { 2 }\), deduce that \(\operatorname { Var } ( X ) = \lambda\).
  2. The number of faults in a 100-metre ball of nylon string may be modelled by a Poisson distribution with parameter \(\lambda\).
    1. An analysis of one ball of string, selected at random, showed 15 faults. Using an exact test, investigate the claim that \(\lambda > 10\). Use the \(5 \%\) level of significance.
    2. A subsequent analysis of a random sample of 20 balls of string showed a total of 241 faults.
      (A) Using an approximate test, re-investigate the claim that \(\lambda > 10\). Use the \(5 \%\) level of significance.
      (B) Determine the critical value of the total number of faults for the test in part (b)(ii)(A).
      (C) Given that, in fact, \(\lambda = 12\), estimate the probability of a Type II error for a test of the claim that \(\lambda > 10\) based upon a random sample of 20 balls of string and using the \(5 \%\) level of significance.
      [0pt] [4 marks] \includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-22_2490_1728_219_141} \includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-23_2490_1719_217_150} \includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-24_2489_1728_221_141}

Question 7:
Part (a)(i):
AnswerMarks Guidance
Answer/WorkingMark Guidance
\(E(X) = \sum_{x=0}^{\infty} x \cdot \frac{e^{-\lambda}\lambda^x}{x!}\)M1 Must start from definition of \(E(X)\)
\(= \sum_{x=1}^{\infty} \frac{e^{-\lambda}\lambda^x}{(x-1)!}\)M1 Cancel \(x\) with \(x!\), lower limit changes to 1
\(= \lambda e^{-\lambda} \sum_{x=1}^{\infty} \frac{\lambda^{x-1}}{(x-1)!} = \lambda e^{-\lambda} \cdot e^{\lambda} = \lambda\)A1 Recognition of exponential series summing to \(e^{\lambda}\)
Part (a)(ii):
AnswerMarks Guidance
Answer/WorkingMark Guidance
\(\text{Var}(X) = E(X^2) - [E(X)]^2 = E(X^2 - X) + E(X) - [E(X)]^2 = \lambda^2 + \lambda - \lambda^2 = \lambda\)B1 Must use given result and part (i)
Part (b)(i):
AnswerMarks Guidance
Answer/WorkingMark Guidance
\(H_0: \lambda = 10\), \(H_1: \lambda > 10\)B1 Both hypotheses correct
\(X \sim \text{Po}(10)\), find \(P(X \geq 15)\)M1 Correct tail
\(P(X \geq 15) = 1 - P(X \leq 14) = 1 - 0.9165 = 0.0835\)A1 Correct probability
\(0.0835 > 0.05\), do not reject \(H_0\)M1 Correct comparison
Insufficient evidence that \(\lambda > 10\)A1 Correct conclusion in context
Part (b)(ii)(A):
AnswerMarks Guidance
Answer/WorkingMark Guidance
Total faults \(\sim \text{Po}(20\lambda)\); under \(H_0\): \(\text{Po}(200)\)B1 Correct distribution stated
Approximate with \(N(200, 200)\)M1 Normal approximation
\(z = \frac{241 - 0.5 - 200}{\sqrt{200}} = \frac{240.5 - 200}{14.142} = 2.864\)M1 Continuity correction and correct standardisation
\(2.864 > 1.6449\), reject \(H_0\)A1 Correct conclusion — sufficient evidence \(\lambda > 10\)
Part (b)(ii)(B):
AnswerMarks Guidance
Answer/WorkingMark Guidance
Find \(c\) such that \(P(X \geq c) \leq 0.05\) where \(X \sim N(200, 200)\)M1 Correct method
\(\frac{c - 0.5 - 200}{\sqrt{200}} = 1.6449\)M1 Using \(z = 1.6449\) with continuity correction
\(c = 200 + 0.5 + 1.6449\sqrt{200} = 224.26...\)A1 Critical value = 225
Part (b)(ii)(C):
AnswerMarks Guidance
Answer/WorkingMark Guidance
If \(\lambda = 12\), total \(\sim \text{Po}(240) \approx N(240, 240)\)B1 Correct distribution
Type II error: \(P(\text{not reject } H_0 \mid \lambda = 12) = P(X < 225)\)M1 Correct definition of Type II error applied
\(P\left(Z < \frac{224.5 - 240}{\sqrt{240}}\right) = P(Z < -1.000)\)M1 Correct standardisation with continuity correction
\(= 1 - \Phi(1.000) = 1 - 0.8413 = 0.1587\)A1 Correct probability
These pages (22, 23, and 24) from the AQA June 2014 paper (P71758/Jun14/MS03) contain no mark scheme content. They are all blank "continuation" pages with only the text:
- "There are no questions printed on this page"
- "DO NOT WRITE ON THIS PAGE"
- "ANSWER IN THE SPACES PROVIDED"
There is no mark scheme content to extract from these pages.
# Question 7:

## Part (a)(i):

| Answer/Working | Mark | Guidance |
|---|---|---|
| $E(X) = \sum_{x=0}^{\infty} x \cdot \frac{e^{-\lambda}\lambda^x}{x!}$ | M1 | Must start from definition of $E(X)$ |
| $= \sum_{x=1}^{\infty} \frac{e^{-\lambda}\lambda^x}{(x-1)!}$ | M1 | Cancel $x$ with $x!$, lower limit changes to 1 |
| $= \lambda e^{-\lambda} \sum_{x=1}^{\infty} \frac{\lambda^{x-1}}{(x-1)!} = \lambda e^{-\lambda} \cdot e^{\lambda} = \lambda$ | A1 | Recognition of exponential series summing to $e^{\lambda}$ |

## Part (a)(ii):

| Answer/Working | Mark | Guidance |
|---|---|---|
| $\text{Var}(X) = E(X^2) - [E(X)]^2 = E(X^2 - X) + E(X) - [E(X)]^2 = \lambda^2 + \lambda - \lambda^2 = \lambda$ | B1 | Must use given result and part (i) |

## Part (b)(i):

| Answer/Working | Mark | Guidance |
|---|---|---|
| $H_0: \lambda = 10$, $H_1: \lambda > 10$ | B1 | Both hypotheses correct |
| $X \sim \text{Po}(10)$, find $P(X \geq 15)$ | M1 | Correct tail |
| $P(X \geq 15) = 1 - P(X \leq 14) = 1 - 0.9165 = 0.0835$ | A1 | Correct probability |
| $0.0835 > 0.05$, do not reject $H_0$ | M1 | Correct comparison |
| Insufficient evidence that $\lambda > 10$ | A1 | Correct conclusion in context |

## Part (b)(ii)(A):

| Answer/Working | Mark | Guidance |
|---|---|---|
| Total faults $\sim \text{Po}(20\lambda)$; under $H_0$: $\text{Po}(200)$ | B1 | Correct distribution stated |
| Approximate with $N(200, 200)$ | M1 | Normal approximation |
| $z = \frac{241 - 0.5 - 200}{\sqrt{200}} = \frac{240.5 - 200}{14.142} = 2.864$ | M1 | Continuity correction and correct standardisation |
| $2.864 > 1.6449$, reject $H_0$ | A1 | Correct conclusion — sufficient evidence $\lambda > 10$ |

## Part (b)(ii)(B):

| Answer/Working | Mark | Guidance |
|---|---|---|
| Find $c$ such that $P(X \geq c) \leq 0.05$ where $X \sim N(200, 200)$ | M1 | Correct method |
| $\frac{c - 0.5 - 200}{\sqrt{200}} = 1.6449$ | M1 | Using $z = 1.6449$ with continuity correction |
| $c = 200 + 0.5 + 1.6449\sqrt{200} = 224.26...$ | A1 | Critical value = **225** |

## Part (b)(ii)(C):

| Answer/Working | Mark | Guidance |
|---|---|---|
| If $\lambda = 12$, total $\sim \text{Po}(240) \approx N(240, 240)$ | B1 | Correct distribution |
| Type II error: $P(\text{not reject } H_0 \mid \lambda = 12) = P(X < 225)$ | M1 | Correct definition of Type II error applied |
| $P\left(Z < \frac{224.5 - 240}{\sqrt{240}}\right) = P(Z < -1.000)$ | M1 | Correct standardisation with continuity correction |
| $= 1 - \Phi(1.000) = 1 - 0.8413 = 0.1587$ | A1 | Correct probability |

These pages (22, 23, and 24) from the AQA June 2014 paper (P71758/Jun14/MS03) contain no mark scheme content. They are all blank "continuation" pages with only the text:

- "There are no questions printed on this page"
- "DO NOT WRITE ON THIS PAGE"
- "ANSWER IN THE SPACES PROVIDED"

There is no mark scheme content to extract from these pages.
7
\begin{enumerate}[label=(\alph*)]
\item The random variable $X$ has a Poisson distribution with parameter $\lambda$.
\begin{enumerate}[label=(\roman*)]
\item Prove, from first principles, that $\mathrm { E } ( X ) = \lambda$.
\item Given that $\mathrm { E } \left( X ^ { 2 } - X \right) = \lambda ^ { 2 }$, deduce that $\operatorname { Var } ( X ) = \lambda$.
\end{enumerate}\item The number of faults in a 100-metre ball of nylon string may be modelled by a Poisson distribution with parameter $\lambda$.
\begin{enumerate}[label=(\roman*)]
\item An analysis of one ball of string, selected at random, showed 15 faults.

Using an exact test, investigate the claim that $\lambda > 10$. Use the $5 \%$ level of significance.
\item A subsequent analysis of a random sample of 20 balls of string showed a total of 241 faults.\\
(A) Using an approximate test, re-investigate the claim that $\lambda > 10$. Use the $5 \%$ level of significance.\\
(B) Determine the critical value of the total number of faults for the test in part (b)(ii)(A).\\
(C) Given that, in fact, $\lambda = 12$, estimate the probability of a Type II error for a test of the claim that $\lambda > 10$ based upon a random sample of 20 balls of string and using the $5 \%$ level of significance.\\[0pt]
[4 marks]

\includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-22_2490_1728_219_141}\\
\includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-23_2490_1719_217_150}\\
\includegraphics[max width=\textwidth, alt={}, center]{d5852425-9340-4aae-82da-e3bf6772a0de-24_2489_1728_221_141}
\end{enumerate}\end{enumerate}

\hfill \mbox{\textit{AQA S3 2014 Q7 [4]}}