The Mann-Whitney U test is non-parametric and is analogous to which parametric test for independent samples?

The Mann-Whitney U test is non-parametric and is analogous to which parametric test for independent samples?

• A. t-test for Independent Samples
• B. Paired t-test
• C. One-way ANOVA
• D. Chi-Square Test

Answer: (A)

The main idea here is that the Mann-Whitney U test is the nonparametric stand-in for the independent-samples t-test. It’s used when you have two unrelated groups and you can’t assume normal distributions. Instead of comparing means, it ranks all observations from both groups together and then compares the average ranks of the two groups. A difference in distributions shows up as a difference in ranks, which the test assesses with a p-value. That’s why the independent-samples t-test is the best match: both are about comparing two separate groups, but one uses raw data under normality (the t-test) while the other uses ranks without that assumption (Mann-Whitney). The Paired t-test is for related or matched samples, not independent groups. One-way ANOVA handles more than two groups (and its nonparametric cousin is Kruskal-Wallis). The Chi-square test deals with categorical data, not a continuous outcome analyzed via rank-based methods.

The main idea here is that the Mann-Whitney U test is the nonparametric stand-in for the independent-samples t-test. It’s used when you have two unrelated groups and you can’t assume normal distributions. Instead of comparing means, it ranks all observations from both groups together and then compares the average ranks of the two groups. A difference in distributions shows up as a difference in ranks, which the test assesses with a p-value.

That’s why the independent-samples t-test is the best match: both are about comparing two separate groups, but one uses raw data under normality (the t-test) while the other uses ranks without that assumption (Mann-Whitney).

The Paired t-test is for related or matched samples, not independent groups. One-way ANOVA handles more than two groups (and its nonparametric cousin is Kruskal-Wallis). The Chi-square test deals with categorical data, not a continuous outcome analyzed via rank-based methods.