It is often difficult, particularly when conducting research in psychology, to have access to large normally distributed samples. Fortunately, there are statistical tests to compare two independent groups that do not require large normally distributed samples. The Mann-Whitney U is one of these tests. In the following work, a summary of this test is presented. The explanation of the logic underlying this test and its application are presented. Moreover, the forces and weaknesses of the Mann-Whitney U are mentioned. One major limit of the Mann-Whitney U is that the type I error or alpha (α) is amplified in a situation of heteroscedasticity.

It is generally recognized that psychological studies often involve small samples. For example, researchers in clinical psychology often have to deal with small samples that generally include less than 15 participants (Kazdin 2003; Shapiro & Shapiro, 1983; Kraemer, 1981; Kazdin, 1986). Although the researchers aim at collecting large normally distributed samples, they rarely have the appropriate amount of resources (time and money) to recruit a sufficient number of participants. It is thus useful, particularly in psychology, to consider tests that have few constraints and allow experimenters to test their hypotheses on small and poorly distributed samples.