Wilcoxon-Signed Rank and Wilcoxon Rank-Sum Tests for Testing Hypotheses on Dependent and Independent Populations
The tests essentially calculate the difference between sets of pairs and analyzes these differences to establish if they are statistically significantly different from one another.
The first step of the Wilcoxon sign test is to calculate the differences of the repeated measurements and to calculate the absolute differences.
Moreover, the analysis plays an alternative means of assessment to the paired Student’s test for corresponding pairs as well as the t-test for independent samples in the event that the populace is not normally distributed. In carrying out the Wilcoxon test, the statistics from the corresponding population are paired off. The test also applies random sampling of the independent pairs (Gravetter & Wallnau, 2009). Moreover, an ordinal scale is vital in measuring the statistics following a normal distribution. In essence, the hypothesis testing of non-parametric data is essential in assessing records that can be placed in a given order but lack the statistical figures. In fact, the test is invaluable in analyzing clientele fulfillment (Gravetter & Wallnau, 2009).
can take only a finite number of values). Otherwise, it would lead to a too computationally expensive algorithm. Finding a low computational cost algorithm for extending the generalized Wilcoxon rank-sum test remains an open problem.
Cleves, M. A. (2008). An introduction to survival analysis using stata. New York, NY: Stata Press.
Gravetter, F. J. & Wallnau, L. B. (2009). Statistics for the behavioral sciences. Belmont, CA: Cengage Learning.