| Exam Board | OCR MEI |
|---|---|
| Module | S3 (Statistics 3) |
| Year | 2010 |
| Session | June |
| Marks | 18 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | T-tests (unknown variance) |
| Type | Single sample t-test |
| Difficulty | Standard +0.3 This is a standard S3 hypothesis testing question requiring a one-sample t-test with straightforward calculations (mean, standard deviation, test statistic) and interpretation. While it has multiple parts worth 18 marks total, each component follows routine procedures taught in the module with no novel problem-solving required. The calculations are slightly tedious but mechanical, making it slightly easier than average for an A-level statistics question. |
| Spec | 5.05c Hypothesis test: normal distribution for population mean5.05d Confidence intervals: using normal distribution |
| Answer | Marks |
|---|---|
| B1 | [3] |
| B1 | |
| B1 |
| Answer | Marks |
|---|---|
| B1 | Both hypotheses. Hypotheses in words only must include "population". Do NOT allow "\(\bar{X} = ...\)" or similar unless \(\bar{X}\) is clearly and explicitly stated to be a population mean. |
| B1 | For adequate verbal definition. Allow absence of "population" if correct notation is used. |
| Answer | Marks |
|---|---|
| B1 | \(s_n = 0.006746\) but do NOT allow this here or in construction of test statistic, but FT from there. |
| M1 | Allow c's \(\bar{x}\) and/or \(s_{n-1}\). Allow alternative: \(1.040 + (c's \cdot 1.860) \times \frac{0.007155}{\sqrt{9}}\) (= 1.0444) for subsequent comparison with \(\bar{x}\). (Or \(\bar{x} - (c's \cdot 860) \times \frac{0.007155}{\sqrt{9}}\) (= 1.0407) for comparison with 1.040.) c.a.o. but ft from here in any case if wrong. |
| Answer | Marks |
|---|---|
| M1 | No ft from here if wrong. |
| Answer | Marks |
|---|---|
| A1 | \(P(r > 2.1896) = 0.05996.\) No ft from here if wrong. |
| A1 | If only c's test statistic. |
| A1 | If only c's test statistic. |
| Answer | Marks |
|---|---|
| M1 | |
| B1 | |
| M1 | |
| A1 | c.a.o. Must be expressed as an interval. ZERO/4 if not same distribution as test. Same wrong distribution scores maximum M1B0M1A0. Recovery to \(t_8\) is OK. |
| E2 | E2, 1, 0. |
## Part (i)
A t test might be used because:
- sample is small
- population variance is unknown
- Must assume background population is Normal.
| B1 | [3]
| B1 |
| B1 |
## Part (ii)
$H_0: \mu = 1.040$
$H_1: \mu \neq 1.040$
where $\mu$ is the mean specific gravity of the mixture.
| B1 | Both hypotheses. Hypotheses in words only must include "population". Do NOT allow "$\bar{X} = ...$" or similar unless $\bar{X}$ is clearly and explicitly stated to be a population mean. |
| B1 | For adequate verbal definition. Allow absence of "population" if correct notation is used. |
$\bar{x} = 1.0452$, $s_{n-1} = 0.007155$
Test statistic is $\frac{1.0452 - 1.040}{0.007155/\sqrt{9}} = 2.189(60)$.
| B1 | $s_n = 0.006746$ but do NOT allow this here or in construction of test statistic, but FT from there. |
| M1 | Allow c's $\bar{x}$ and/or $s_{n-1}$. Allow alternative: $1.040 + (c's \cdot 1.860) \times \frac{0.007155}{\sqrt{9}}$ (= 1.0444) for subsequent comparison with $\bar{x}$. (Or $\bar{x} - (c's \cdot 860) \times \frac{0.007155}{\sqrt{9}}$ (= 1.0407) for comparison with 1.040.) c.a.o. but ft from here in any case if wrong. |
Refer to $t_8$.
| M1 | No ft from here if wrong. |
Double-tailed 10% point is 1.860.
Significant.
Seems mean specific gravity in the mixture does not meet the requirement.
| A1 | $P(r > 2.1896) = 0.05996.$ No ft from here if wrong. |
| A1 | If only c's test statistic. |
| A1 | If only c's test statistic. |
[9]
## Part (iii)
CI is given by:
$$1.0452 \pm \frac{2.306 \times 0.007155}{\sqrt{9}} = 1.0452 \pm 0.0055 = (1.039(7), 1.050(7))$$
In repeated sampling, 95% of confidence intervals constructed in this way will contain the true population mean.
| M1 | |
| B1 | |
| M1 | |
| A1 | c.a.o. Must be expressed as an interval. ZERO/4 if not same distribution as test. Same wrong distribution scores maximum M1B0M1A0. Recovery to $t_8$ is OK. |
| E2 | E2, 1, 0. |
[6]
---
William Sealy, a biochemistry student, is doing work experience at a brewery. One of his tasks is to monitor the specific gravity of the brewing mixture during the brewing process. For one particular recipe, an initial specific gravity of 1.040 is required. A random sample of 9 measurements of the specific gravity at the start of the process gave the following results.
1.046 \quad 1.048 \quad 1.039 \quad 1.055 \quad 1.038 \quad 1.054 \quad 1.038 \quad 1.051 \quad 1.038
\begin{enumerate}[label=(\roman*)]
\item William has to test whether the specific gravity of the mixture meets the requirement. Why might a $t$ test be used for these data and what assumption must be made? [3]
\item Carry out the test using a significance level of 10\%. [9]
\item Find a 95\% confidence interval for the true mean specific gravity of the mixture and explain what is meant by a 95\% confidence interval. [6]
\end{enumerate}
\hfill \mbox{\textit{OCR MEI S3 2010 Q2 [18]}}