Question 1

What is the difference between parametric and non-parametric tests in psychology?

Accepted Answer

Parametric tests (e.g., t-tests, Pearson’s r) require interval-level data and assumptions such as normal distribution and homogeneity of variance. They are more powerful, meaning they are better at detecting a genuine effect. Non-parametric tests (e.g., Mann–Whitney, Wilcoxon, Spearman’s rho) are used with ordinal or nominal data, or when parametric assumptions are violated. They rank data rather than using raw scores. In AQA A-Level, you are not required to test parametric assumptions but must choose the test based on the level of measurement and design. As a rule of thumb, if you have ordinal data, select a non-parametric counterpart.

Question 2

How do I know which statistical test to use in AQA Psychology?

Accepted Answer

Follow a three-step decision tree: (1) Are you testing for a difference or a correlation? (2) What is the experimental design – independent groups, repeated measures, or matched pairs? (3) What level of measurement does your data have? For example, for a difference with independent groups and ordinal data, use Mann–Whitney U; for a correlation with ordinal data, use Spearman’s rho; for nominal data, use Chi-squared (which is for frequencies or categories). Always memorise the AQA test list (Chi-squared, Mann–Whitney, Wilcoxon, Spearman’s rho, related t-test, unrelated t-test, Pearson’s r) and practise applying the flowchart to past paper scenarios.

Question 3

What does a p-value of 0.03 actually mean?

Accepted Answer

A p-value of 0.03 means that if the null hypothesis were true (i.e., there is no real effect in the population), the probability of obtaining your observed results (or more extreme results) purely by chance is 3%. Since this is less than the conventional significance level of 0.05, you would reject the null hypothesis and conclude that your results are statistically significant. It does not mean there is a 3% chance the null hypothesis is correct, nor does it tell you the size or importance of the effect – only that the result is unlikely to have occurred by chance.

Question 4

What is a Type I error and how can I avoid it?

Accepted Answer

A Type I error occurs when you reject the null hypothesis even though it is true – essentially a false positive. You conclude there is a significant effect when in reality there isn’t one. This risk is directly related to the significance level: if you test at p ≤ 0.05, there is a 5% probability of a Type I error. To reduce the risk, researchers may adopt a stricter significance level, such as p ≤ 0.01. However, this increases the chance of a Type II error. In exam answers, always acknowledge this trade-off and the context of the research.

Question 5

Why do we use the 0.05 significance level in psychology?

Accepted Answer

The 0.05 significance level (p ≤ 0.05) is a conventional threshold balancing the risks of Type I and Type II errors. It means there is a 5% risk of falsely claiming an effect exists when it doesn’t. This level was popularised by statistician Ronald Fisher and has become standard in psychology because it offers a reasonable compromise: it’s strict enough to protect against false positives while not being so strict that it routinely misses genuine effects. In AQA exams, you may need to explain that p ≤ 0.05 is acceptable unless a more conservative level is justified (e.g., in medical trials).

Question 6

How do I use a critical value table for the Mann–Whitney U test?

Accepted Answer

For the Mann–Whitney U test, you have two groups with sample sizes n1 and n2. Locate the smaller of your two calculated U values (from your analysis). In the critical value table, find the row and column corresponding to n1 and n2 at your chosen significance level (usually p ≤ 0.05) and whether the hypothesis is one- or two-tailed. The table gives a critical value. To be significant, your calculated U must be equal to or less than the critical value (note: this is the opposite of many other tests). If it is, reject the null hypothesis. Always double-check the direction specified in the table, as different tables may vary.

Inferential testing

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Related Topics in AQA A-Level Psychology

Addiction

Aggression

Approaches in Psychology

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How to Revise Inferential testing — AQA A-Level Psychology

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