A statistical procedure used to compare two independent samples to assess whether their population distributions are equal. This non-parametric test evaluates the null hypothesis that two populations are identical against an alternative hypothesis that specifies a difference in location. Implementation of this test frequently involves a programming language such as Python, leveraging libraries like SciPy for efficient computation. For instance, given two datasets representing scores from different groups, the procedure can determine if one group tends to have larger values than the other, without assuming a specific distribution form.
The value of this statistical method lies in its robustness when dealing with non-normally distributed data or ordinal scale measurements. This characteristic makes it a valuable tool across various disciplines, from medical research to social sciences, where distributional assumptions are often violated. Historically, the test offered a practical alternative to parametric methods, expanding the scope of statistical analysis to datasets previously deemed unsuitable for traditional techniques.
