This statistical software analyzes variations between two associated samples, assessing whether or not their inhabitants medians differ considerably. For instance, it may very well 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 method accounts for the magnitude and path of adjustments.
Non-parametric checks like this are useful when knowledge does not meet the assumptions of normality required for parametric checks just like the paired t-test. This expands the applicability of statistical evaluation to a wider vary of datasets, significantly in fields like drugs, psychology, and social sciences the place usually distributed knowledge can not at all times be assured. Developed by Frank Wilcoxon, this technique gives a sturdy different for evaluating paired knowledge.
