A dependent variable measured on a continuous scale has a markedly skewed distribution. Which statistical test is MOST appropriate to detect a difference between two groups?

A dependent variable measured on a continuous scale has a markedly skewed distribution. Which statistical test is MOST appropriate to detect a difference between two groups?

• A. Mann-Whitney U test
• B. Paired t-test
• C. Chi-square test
• D. Analysis of variance

Answer: (A)

When a continuous outcome is markedly skewed, not meeting the normality assumption, a nonparametric approach is preferred for comparing two groups. The Mann-Whitney U test handles this by ranking all observations from both groups together and then comparing the average ranks between the groups. This method does not rely on normality or equal variances and is robust to outliers, making it well suited to detect a difference in the distribution or central tendency between two independent groups when the data are skewed. In contrast, a paired t-test is for related or matched samples, not two independent groups. The chi-square test is for categorical data, not a continuous outcome. Analysis of variance is a parametric method that compares means across groups and assumes normality of residuals; with a skewed distribution, its assumptions are violated, and a nonparametric alternative is more appropriate.

When a continuous outcome is markedly skewed, not meeting the normality assumption, a nonparametric approach is preferred for comparing two groups. The Mann-Whitney U test handles this by ranking all observations from both groups together and then comparing the average ranks between the groups. This method does not rely on normality or equal variances and is robust to outliers, making it well suited to detect a difference in the distribution or central tendency between two independent groups when the data are skewed.

In contrast, a paired t-test is for related or matched samples, not two independent groups. The chi-square test is for categorical data, not a continuous outcome. Analysis of variance is a parametric method that compares means across groups and assumes normality of residuals; with a skewed distribution, its assumptions are violated, and a nonparametric alternative is more appropriate.