A2 June 2023 Q5
5. A psychologist claims to have developed a technique to improve a person’s memory.
A random sample of 8 people are each given the same list of words to memorise and recall.
Each person then receives memory training from the psychologist. After the training, each person is given the same list of new words to memorise and recall.
The table shows the percentage of words recalled by each person before and after the training.
| Person | \(A\) | \(B\) | \(C\) | \(D\) | \(E\) | \(F\) | \(G\) | \(H\) |
|---|---|---|---|---|---|---|---|---|
| Percentage of words recalled before training | 24 | 33 | 33 | 39 | 30 | 38 | 32 | 34 |
| Percentage of words recalled after training | 28 | 30 | 37 | 41 | 32 | 44 | 35 | 34 |
State your hypotheses, test statistic and critical value used for this test. (7)
| Scheme | Marks | AO |
|---|---|---|
| e.g. for each person the scores before and after are not independent | B1 | 2.4 |
| (1) |
Notes
B1: correct explanation
| Scheme | Marks | AO |
|---|---|---|
| The differences in scores are normally distributed. | B1 | 2.4 |
| (1) |
Notes
B1: correct modelling assumption
| Scheme | Marks | AO |
|---|---|---|
| \(d\): \(4\quad -3\quad 4\quad 2\quad 2\quad 6\quad 3\quad 0\) | M1 | 3.1b |
| \(\bar{d} = \pm 2.25 \qquad s_d = \sqrt{7.642857\ldots} = 2.76457\ldots\) | M1 | 1.1b |
| \(\mathrm{H}_0 : \mu_\mathrm{d} = 0 \qquad \mathrm{H}_1 : \mu_\mathrm{d} \gt 0\) | B1 | 3.3 |
| \(t = \pm\dfrac{\text{“}\pm 2.25\text{”}}{\frac{\text{“}2.76\ldots\text{”}}{\sqrt{8}}}\) | M1 | 1.1b |
| \(= \pm 2.3019\ldots\) awrt \(\boldsymbol{\pm 2.30}\) | A1 | 1.1b |
| Critical value \(t_7 = \pm 1.895\) | B1 | 1.1b |
| 2.30 > 1.895, therefore (reject H0) there is sufficient evidence to: support an increase in the percentage of words recalled or support psychologist’s claim | A1ft | 2.2b |
| (7) | ||
| (9 marks) |
Notes
M1: for setting up paired \(t\)-test with at least 5 correct differences consistent in direction
M1: complete method for \(\bar{d}\) and \(s_\mathrm{d}\) or \(s_d^{\,2}\)
B1: Use of \(t\)-distribution for differences with both hypotheses correct in terms of \(\mu\) / \(\mu_\mathrm{d}\)
Allow \(\mu_\mathrm{d} \lt 0\) if candidate does test with negative test statistic
M1: method for finding test statistic with their values
A1: awrt \(\pm\)2.30
B1: correct critical \(\pm\)1.895 (or better) with compatible sign
A1ft: drawing a correct inference in context
Must be consistent with their CV and a standardised test statistic from \(t\)-distribution
Must mention “percentage” and “words” or “psychologist’s claim”
SC: If they have carried out a \(t\)-test for two independent samples they can potentially score: M0M0B0M1A0B1A1ft
If they do follow this path, they can score:
3rd M1 for standardising with difference of their means and a pooled variance
2nd B1 for a CV of 1.761
A1ft for a correct contextual conclusion for their test statistic and 1.761