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When would you use the Mann-Whitney test?

  1. When comparing two sets of nominal data

  2. When comparing two independent groups with ordinal or continuous data

  3. In repeated measures designs with nominal data

  4. For testing the goodness of fit

The correct answer is: When comparing two independent groups with ordinal or continuous data

The Mann-Whitney test is specifically designed to compare two independent groups when the data being analyzed is either ordinal or continuous but does not necessarily follow a normal distribution. This statistical test is a non-parametric alternative to the t-test and is particularly useful when the assumptions of normality and homogeneity of variance required for parametric tests cannot be met. In practice, the Mann-Whitney test ranks all the data points from both groups combined and then compares the sum ranks between the two groups. This approach allows researchers to determine if there is a significant difference in distributions between the two independent groups, making it appropriate for various research scenarios where the data may not be suitable for parametric tests. This contrasts sharply with scenarios involving nominal data or repeated measures designs, which are addressed by different statistical tests. For example, nominal data typically involves counts or categories, making tests like the Chi-squared test more appropriate. Therefore, the focus of the Mann-Whitney test on rank data from independent groups with ordinal or continuous measures highlights its relevance and utility in specific research contexts.