This statistical hypothesis test assesses whether two independent samples originate from the same distribution. Specifically, it determines if there is a significant difference between the medians of the two populations from which the samples were drawn. For example, a researcher might employ this test to compare the effectiveness of two different teaching methods by analyzing student test scores from each method’s respective group. The letter “u” is sometimes, but not always, included in the naming convention. Software packages, including those accessible through the R programming language, provide functionalities to perform this analysis.
The application of this non-parametric test is particularly valuable when data do not meet the assumptions required for parametric tests, such as the t-test (specifically, normality). Its utility extends to situations where the data are ordinal, or when outliers are present. Historically, it emerged as a powerful alternative to parametric methods, offering robustness in scenarios where distributional assumptions are questionable. The accessibility of implementation within the R environment further enhances its practicality, facilitating widespread adoption across diverse research fields.
