Which nonparametric test is used to compare two independent groups?

Which nonparametric test is used to compare two independent groups?

• A. Independent t-test
• B. Mann-Whitney U test
• C. Paired t-test
• D. ANOVA

Answer: (B)

When you want to compare two independent groups without assuming that the data are normally distributed, you use a rank-based, nonparametric approach. The Mann-Whitney U test fits this need by ranking all observations from both groups together and then comparing the sums of those ranks between the groups. Because it relies on ranks rather than actual values, it doesn’t require normality or equal variances and is robust to outliers, making it appropriate for skewed data or small samples. Its null hypothesis is that the two groups come from the same distribution, so a significant result indicates a systematic difference between groups in their distributions. If the shapes of the distributions are similar, this difference often reflects a difference in central tendency (like medians). This is the best choice among the options for two independent groups when the data may violate parametric assumptions. In contrast, the independent t-test assumes normality and equal variances; the paired t-test is for related or matched samples; and ANOVA is used for more than two groups and also assumes normality.

When you want to compare two independent groups without assuming that the data are normally distributed, you use a rank-based, nonparametric approach. The Mann-Whitney U test fits this need by ranking all observations from both groups together and then comparing the sums of those ranks between the groups. Because it relies on ranks rather than actual values, it doesn’t require normality or equal variances and is robust to outliers, making it appropriate for skewed data or small samples.

Its null hypothesis is that the two groups come from the same distribution, so a significant result indicates a systematic difference between groups in their distributions. If the shapes of the distributions are similar, this difference often reflects a difference in central tendency (like medians).

This is the best choice among the options for two independent groups when the data may violate parametric assumptions. In contrast, the independent t-test assumes normality and equal variances; the paired t-test is for related or matched samples; and ANOVA is used for more than two groups and also assumes normality.