The Mann-Whitney test is best described as

The Mann-Whitney test is best described as

• A. A non-parametric test that compares two independent samples.
• B. A parametric test comparing means of related samples.
• C. A non-parametric test for more than two groups.
• D. A test for equality of variances.

Answer: (A)

The main idea is that the Mann-Whitney test is a non-parametric method used when you want to compare two independent groups without assuming normality. It works by ranking all observations from both groups together and evaluating whether one group tends to have higher (or lower) values than the other based on those ranks. Because it relies on ranks rather than raw data, it doesn’t require the data to be normally distributed and it doesn’t assume equal variances. It’s suited for independent samples, not paired or related samples, and it’s not designed for more than two groups. It also isn’t a test for equality of variances. Therefore, the description that matches is a non-parametric test that compares two independent samples.

The main idea is that the Mann-Whitney test is a non-parametric method used when you want to compare two independent groups without assuming normality. It works by ranking all observations from both groups together and evaluating whether one group tends to have higher (or lower) values than the other based on those ranks. Because it relies on ranks rather than raw data, it doesn’t require the data to be normally distributed and it doesn’t assume equal variances. It’s suited for independent samples, not paired or related samples, and it’s not designed for more than two groups. It also isn’t a test for equality of variances. Therefore, the description that matches is a non-parametric test that compares two independent samples.