This statistical device analyzes variations between two associated samples, assessing whether or not their inhabitants medians differ considerably. For instance, it might be used to match pre- and post-treatment measurements on the identical people to find out therapy effectiveness. The evaluation ranks absolutely the variations between paired observations, then sums the ranks of optimistic and damaging variations individually. This strategy accounts for the magnitude and route of modifications.
Non-parametric assessments like this are beneficial when knowledge does not meet the assumptions of normality required for parametric assessments just like the paired t-test. This expands the applicability of statistical evaluation to a wider vary of datasets, notably in fields like drugs, psychology, and social sciences the place usually distributed knowledge can’t all the time be assured. Developed by Frank Wilcoxon, this technique affords a sturdy various for evaluating paired knowledge.
