The Mann-Whitney U test is a non-parametric statistical procedure designed to assess differences between two independent samples by analyzing rank-order data rather than raw scores, serving as the theoretical counterpart to the parametric t-test for independent means within inferential statistics and behavioral sciences. APA reporting standards for this concept mandate the formal specification of the test statistic (U), sample sizes (n1/n2), exact p-values or significance thresholds, effect size metrics (such as r) with magnitude interpretations, and a contextualized summary of findings to ensure rigorous scientific communication. This theoretical framework emphasizes clarity in defining null hypotheses regarding distribution differences while strictly adhering to standardized conventions for presenting abstract statistical evidence without reliance on parametric assumptions about data normality.
The Mann-Whitney U test is a non-parametric statistical procedure designed to assess differences between two independent samples by analyzing rank-order data rather than raw scores, serving as the th…