| Exam Board | OCR |
|---|---|
| Module | S2 (Statistics 2) |
| Year | 2015 |
| Session | June |
| Marks | 13 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | Hypothesis test of a Poisson distribution |
| Type | One-tailed test (increase or decrease) |
| Difficulty | Standard +0.3 This is a standard S2 hypothesis testing question with two parts: (i) a routine one-tailed Poisson test requiring calculation of P(X≤2) under λ=5, and (ii) applying normal approximation to find a critical value. Both parts follow textbook procedures with no novel insight required, though part (ii) involves slightly more steps including continuity correction and inverse normal calculation. Slightly easier than average due to straightforward application of learned techniques. |
| Spec | 2.05a Hypothesis testing language: null, alternative, p-value, significance5.02i Poisson distribution: random events model5.02j Poisson formula: P(X=x) = e^(-lambda)*lambda^x/x!5.02k Calculate Poisson probabilities5.04a Linear combinations: E(aX+bY), Var(aX+bY) |
| Answer | Marks | Guidance |
|---|---|---|
| Answer | Marks | Guidance |
| \(H_0: \lambda = 5\) (1 or \(\frac{1}{3}\)), \(H_1: \lambda < 5\) (1 or \(\frac{1}{3}\)) | B2 | One error, B1, except \(t\), \(x\) etc: 0. Allow \(\mu\) |
| \(\text{Po}(5)\) | M1 | Stated or implied |
| \(P(\leq 2) = \mathbf{0.1247}\) | A1 | |
| \(> 0.05\) | A1 | |
| \(\beta\): CR is \(\leq 1\) and compare 2 explicitly, \(p = 0.0404\) | A1*, dep*A1 | |
| Do not reject \(H_0\). Insufficient evidence of reduction in mean number of points failures | M1, A1ft | Correct first conclusion, needs \(\text{Po}(5)\). Contextualised, acknowledge uncertainty. FT on wrong CR/\(p\)/comparison value |
| Total: 7 |
| Answer | Marks | Guidance |
|---|---|---|
| Answer | Marks | Guidance |
| \(\text{Po}(50) \approx N(50, 50)\) | M1, M1 | Stated or implied. Normal, mean \(150\lambda\) |
| A1 | Variance/sd same | |
| \(50 - 0.5 - 1.645\times\sqrt{50}\) | M1 | \(50 - z\times\sqrt{50}\), *not* \(\div\sqrt{n}\), allow \(\sqrt{}\) error, any cc |
| \(= 37.87\) | A1 | \(z = 1.645\), need \(\sqrt{50}\), allow \(50 + 0.5\) or 50 |
| so maximum number is 37 | A1 | 37 only, from cc, *not* final answer 37.86, but allow corrected to 37 after check |
| Total: 6 | 38(.36) from no cc is probably 5/6. Exact Poisson \((0.0473 \Rightarrow 38)\) is 1/6 |
## Question 7:
### Part (i):
| Answer | Marks | Guidance |
|--------|-------|----------|
| $H_0: \lambda = 5$ (1 or $\frac{1}{3}$), $H_1: \lambda < 5$ (1 or $\frac{1}{3}$) | B2 | One error, B1, except $t$, $x$ etc: 0. Allow $\mu$ |
| $\text{Po}(5)$ | M1 | Stated or implied |
| $P(\leq 2) = \mathbf{0.1247}$ | A1 | |
| $> 0.05$ | A1 | |
| $\beta$: CR is $\leq 1$ and compare 2 explicitly, $p = 0.0404$ | A1*, dep*A1 | |
| Do not reject $H_0$. Insufficient evidence of reduction in mean number of points failures | M1, A1ft | Correct first conclusion, needs $\text{Po}(5)$. Contextualised, acknowledge uncertainty. FT on wrong CR/$p$/comparison value |
| **Total: 7** | | |
### Part (ii):
| Answer | Marks | Guidance |
|--------|-------|----------|
| $\text{Po}(50) \approx N(50, 50)$ | M1, M1 | Stated or implied. Normal, mean $150\lambda$ |
| | A1 | Variance/sd same |
| $50 - 0.5 - 1.645\times\sqrt{50}$ | M1 | $50 - z\times\sqrt{50}$, *not* $\div\sqrt{n}$, allow $\sqrt{}$ error, any cc |
| $= 37.87$ | A1 | $z = 1.645$, need $\sqrt{50}$, allow $50 + 0.5$ or 50 |
| so maximum number is **37** | A1 | 37 only, from cc, *not* final answer 37.86, but allow corrected to 37 after check |
| **Total: 6** | | 38(.36) from no cc is probably 5/6. Exact Poisson $(0.0473 \Rightarrow 38)$ is 1/6 |
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7 A large railway network suffers points failures at an average rate of 1 every 3 days. Assume that the number of points failures can be modelled by a Poisson distribution. The network employs a new firm of engineers. After the new engineers have become established, it is found that in a randomly chosen period of 15 days there are 2 instances of points failures.\\
(i) Test, at the $5 \%$ significance level, whether there is evidence that the mean number of points failures has been reduced.\\
(ii) A new test is carried out over a period of 150 days. Use a suitable approximation to find the greatest number of points failures there could be in 150 days that would lead to a $5 \%$ significance test concluding that the average number of points failures had been reduced.
\hfill \mbox{\textit{OCR S2 2015 Q7 [13]}}