CAIE S2 2017 June — Question 6 14 marks

Exam BoardCAIE
ModuleS2 (Statistics 2)
Year2017
SessionJune
Marks14
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Mark schemeDownload PDF ↗
TopicHypothesis test of a Poisson distribution
TypeOne-tailed test (increase or decrease)
DifficultyStandard +0.3 This is a standard hypothesis testing question with routine Poisson distribution calculations. Parts (i)-(iii) follow textbook procedures for finding critical regions and conducting one-tailed tests. Part (iv) requires recognizing that sum of Poisson variables is Poisson and using normal approximation, which is a standard Further Maths Statistics technique but straightforward to apply. The question is slightly above average difficulty due to the multi-part nature and requiring normal approximation, but involves no novel problem-solving.
Spec2.05a Hypothesis testing language: null, alternative, p-value, significance2.05c Significance levels: one-tail and two-tail5.02i Poisson distribution: random events model5.02k Calculate Poisson probabilities5.02l Poisson conditions: for modelling

6 The number of sports injuries per month at a certain college has a Poisson distribution. In the past the mean has been 1.1 injuries per month. The principal recently introduced new safety guidelines and she decides to test, at the \(2 \%\) significance level, whether the mean number of sports injuries has been reduced. She notes the number of sports injuries during a 6-month period.
  1. Find the critical region for the test and state the probability of a Type I error.
  2. State what is meant by a Type I error in this context.
  3. During the 6 -month period there are a total of 2 sports injuries. Carry out the test.
  4. Assuming that the mean remains 1.1 , calculate the probability that there will be fewer than 30 sports injuries during a 36-month period.

Question 6(i):
AnswerMarks Guidance
AnswerMarks Guidance
\(\text{mean} = 6.6\)B1 B1 for 6.6 (could be scored in iii)
\(P(X \leqslant 1) = e^{-6.6}(1 + 6.6) = 0.0103\)M1 Allow incorrect \(\lambda\) in both probs
\(P(X \leqslant 2) = e^{-6.6}(1 + 6.6 + \frac{6.6^2}{2}) = 0.0400\)M1A1 A1 for both values
CR is \(X \leqslant 1\)DA1 Dep on at least one M
\(P(\text{Type I error}) = P(X \leqslant 1) = 0.0103\)B1FT FT their \(P(X \leqslant 1)\)
Total:6
Question 6(ii):
AnswerMarks Guidance
AnswerMarks Guidance
Wrongly concluding that (mean) no of (sports) injuries has decreasedB1 Must be in context
Total:1
Question 6(iii):
AnswerMarks Guidance
AnswerMarks Guidance
\(H_0: \lambda = 6.6 \quad H_1: \lambda < 6.6\)B1 Can be scored in (i). Allow \(\mu\) or \(\lambda/1.1\) or 6.6 or \(P(X \leqslant 2) = 0.0400 > 0.02\)
2 not in CRM1
No evidence mean no. of injuries has decreasedA1FT
Total:3
Question 6(iv):
AnswerMarks Guidance
AnswerMarks Guidance
\(N(39.6,\ 39.6)\)B1 May be implied
\(\dfrac{29.5 - 39.6}{\sqrt{39.6}} = -1.605\)M1 Allow with wrong or no cc
\(\Phi(\text{"}-1.605\text{"}) = 1 - \Phi(\text{"1.605"})\)M1 For area consistent with their mean
\(= 0.0543\) (3 sfs)A1
Total:4
## Question 6(i):

| Answer | Marks | Guidance |
|--------|-------|----------|
| $\text{mean} = 6.6$ | **B1** | **B1** for 6.6 (could be scored in iii) |
| $P(X \leqslant 1) = e^{-6.6}(1 + 6.6) = 0.0103$ | **M1** | Allow incorrect $\lambda$ in both probs |
| $P(X \leqslant 2) = e^{-6.6}(1 + 6.6 + \frac{6.6^2}{2}) = 0.0400$ | **M1A1** | **A1** for both values |
| CR is $X \leqslant 1$ | **DA1** | Dep on at least one **M** |
| $P(\text{Type I error}) = P(X \leqslant 1) = 0.0103$ | **B1FT** | FT their $P(X \leqslant 1)$ |
| **Total:** | **6** | |

---

## Question 6(ii):

| Answer | Marks | Guidance |
|--------|-------|----------|
| Wrongly concluding that (mean) no of (sports) injuries has decreased | **B1** | Must be in context |
| **Total:** | **1** | |

---

## Question 6(iii):

| Answer | Marks | Guidance |
|--------|-------|----------|
| $H_0: \lambda = 6.6 \quad H_1: \lambda < 6.6$ | **B1** | Can be scored in (i). Allow $\mu$ or $\lambda/1.1$ or 6.6 or $P(X \leqslant 2) = 0.0400 > 0.02$ |
| 2 not in CR | **M1** | |
| No evidence mean no. of injuries has decreased | **A1FT** | |
| **Total:** | **3** | |

---

## Question 6(iv):

| Answer | Marks | Guidance |
|--------|-------|----------|
| $N(39.6,\ 39.6)$ | **B1** | May be implied |
| $\dfrac{29.5 - 39.6}{\sqrt{39.6}} = -1.605$ | **M1** | Allow with wrong or no cc |
| $\Phi(\text{"}-1.605\text{"}) = 1 - \Phi(\text{"1.605"})$ | **M1** | For area consistent with their mean |
| $= 0.0543$ (3 sfs) | **A1** | |
| **Total:** | **4** | |
6 The number of sports injuries per month at a certain college has a Poisson distribution. In the past the mean has been 1.1 injuries per month. The principal recently introduced new safety guidelines and she decides to test, at the $2 \%$ significance level, whether the mean number of sports injuries has been reduced. She notes the number of sports injuries during a 6-month period.\\
(i) Find the critical region for the test and state the probability of a Type I error.\\

(ii) State what is meant by a Type I error in this context.\\

(iii) During the 6 -month period there are a total of 2 sports injuries. Carry out the test.\\

(iv) Assuming that the mean remains 1.1 , calculate the probability that there will be fewer than 30 sports injuries during a 36-month period.\\

\hfill \mbox{\textit{CAIE S2 2017 Q6 [14]}}