A2 October 2020 Q5
5. A factory produces pins.
An engineer selects 40 independent random samples of 6 pins produced at the factory and records the number of defective pins in each sample.
| Number of defective pins | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|---|
| Observed frequency | 19 | 11 | 7 | 2 | 0 | 1 | 0 |
The engineer suggests that the number of defective pins in a sample of 6 can be modelled using a binomial distribution. Using the information from the sample above, a test is to be carried out at the 10% significance level, to see whether the data are consistent with the engineer’s suggested model.
The value of the test statistic for this test is 2.689
State your hypotheses clearly. (8)
The engineer later discovers that the previously recorded information was incorrect.
The data should have been as follows.
| Number of defective pins | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|---|
| Observed frequency | 19 | 11 | 6 | 3 | 1 | 0 | 0 |
Give reasons for your answer. (3)
| Scheme | Marks | AO |
|---|---|---|
| \(p = \dfrac{(0) + 11 + 14 + 6 + (0) + 5 + (0)}{6 \times 40}\) | M1 | 2.1 |
| \(p = \underline{\mathbf{0.15}}\)* | A1*cso | 1.1b |
| (2) |
Notes
M1: Correct expression for \(p\) (may be seen in stages). Allow \(\tfrac{36}{240}\) but not \(\tfrac{6}{40}\) on its own
A1*cso: \(p = 0.15\) stated and no incorrect working seen
| Scheme | Marks | AO | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\(X \sim \mathrm{B}(6, 0.15)\)
| M1 | 3.4 | ||||||||||||
| Require \(40 \times \mathrm{P}(X \geqslant k) \gt 5\) Exp. frequency for \(X \geqslant 2 = 8.94\ldots\) / \(X \geqslant 3 = 1.89\ldots\) | M1 | 1.1b | ||||||||||||
| Combine last 5 cells / only 3 cells in total | A1 | 2.2a | ||||||||||||
| 2 is subtracted (as there are 2 restrictions) and the proportion used from data (and 1 equal totals) | B1 | 2.4 | ||||||||||||
| \(3 - 2 = 1\) degree of freedom | A1 | 1.1b | ||||||||||||
| \(\mathrm{H}_0\): Binomial distribution is a suitable model \(\mathrm{H}_1\): Binomial distribution is not a suitable model | B1 | 3.4 | ||||||||||||
| Critical value \(\chi^2_{(1, 0.10)} = 2.705\) or 2.706 | B1ft | 1.1b | ||||||||||||
| Test statistic is not in the critical region, insufficient evidence to reject \(\mathrm{H}_0\) (\(2.689 \lt 2.705/6\)) Data are consistent with binomial/engineer’s/suggested model. | B1ft | 3.5a | ||||||||||||
| (8) |
Notes
M1: Attempting to find expected frequencies, at least 2 correct trunc. or rounded 1dp
M1: Recognising need to combine cells (Sight of awrt 8.94 implies M1M1)
A1: Combining cells for \(X \geqslant 2\) (to make 3 cells)
B1: Justifying why 2 is subtracted with \(p\) being calculated from data
A1: 1 degree of freedom
B1: Correct hypotheses (0.15 must not be included) Allow engineer’s model.
B1ft: Correct critical value (ft their df) May see \(\chi^2_{(2, 0.10)} = 4.605\) or \(\chi^2_{(3, 0.10)} = 6.251\)
B1ft: Correct inference (ft comparison of their CV with 2.689).
Condone \(p = 0.15\) included here. Do not allow contradictory statements to score here.
Hypotheses must be correct way round.
| Scheme | Marks | AO |
|---|---|---|
| The total amount/proportion of defective pins remains the same. | M1 | 2.4 |
| The cells for \(X \geqslant 2\) are still combined in the test. | M1 | 1.1b |
| So there is no change to the value of the test statistic. | A1 | 2.2a |
| (3) | ||
| (13 marks) |
Notes
M1: Determining the number (\(N = 36\))/proportion (\(p = 0.15\)) of defective pins has not changed. e.g. \(11 + 12 + 9 + 4 = 36\). But not \(7 + 2 + 1 = 6 + 3 + 1\)
M1: Understanding the cells for \(X \geqslant 2\) are still combined in the test
A1: (dep on both M1s) Concluding that there is no change to the value of the test statistic.