A Level Psychology OCR Practice Exam

Which statistical test is appropriate for testing differences using independent groups with ordinal or continuous data?

1. T-Test

2. Mann-Whitney test

3. Chi-squared test

4. ANOVA

The correct answer is: Mann-Whitney test

The Mann-Whitney test is indeed the appropriate choice for testing differences between independent groups when dealing with ordinal or continuous data. This non-parametric test is specifically designed for situations where the data does not meet the assumptions necessary for parametric tests, such as the t-test or ANOVA, which assume that the data is normally distributed. The Mann-Whitney test evaluates whether the distributions of two independent groups differ significantly without requiring the data to adhere to strict assumptions about the population distribution. It focuses on the ranks of the data rather than the raw scores, making it suitable for ordinal data where the spacing between values cannot be assumed to be equal. In contrast, the t-test would require interval or ratio data and normally distributed samples, making it less suitable for ordinal data. The chi-squared test, while a useful tool for categorical data, does not apply to continuous or ordinal scales in terms of examining differences between independent groups. ANOVA, similarly, is a parametric test intended for comparing means across three or more groups, assuming normally distributed data and equal variances, which does not align with the ideal use case for ordinal data.