Wilcoxon Statistics in R: Signed-Rank Test and Rank-Sum Test

This chapterSigned-Rank providesRank-sum the readers with guideline on how to run the Wilcoxon statistical test in R. The Wilcoxon testWilcoxon test is a non-parametricNon-parametric “alternative test to the t-test” used for comparing the medianMedian of two data samples or variables. This inferential statistical test is particularly recommended in a situation where the dataset the researchers or data analysts want to analyze is not normally distributed or are in a ranked or ordinal scaleOrdinal scale. By definition, Wilcoxon test is one of the inferential (non-parametricNon-parametric) statistics that are used for hypothesis testing, and for determining the significant differences (where applicable) between the “medians” of two independent groups of data or paired variables. The common types of the test in the current literature are, namely, (i) Wilcoxon Signed-RankSigned-Rank and (ii) Wilcoxon Rank-SumRank-sum tests, which are explained and practically illustrated in this chapter. The Wilcoxon Signed-Rank test (also referred to as alternative to the Paired Sample t-test) is calculated based on differences in the samples’ scores but in addition to it taking into account the signs of the differences, thus, takes into consideration the magnitudes of the observed differences. Whereas the Wilcoxon Rank-Sum test (also referred to as alternative to the Independent Sample t-test) is used to compare the medianMedian of two independently sampled data where the condition for conducting the “Independent Sample t-test” is not met or the dataset in question contains outliers (i.e., distribution-free or not normally distributed)Outliers.