Understanding Non-Parametric Hypothesis Testing The Kruskal-Wallis test is a fundamental tool in non-parametric statistics. It is utilized when researchers need to assess whether there are statistically significant differences among the medians of three or more independent groups. This test serves as the non-parametric equivalent of the standard One-Way ANOVA, which typically requires strict assumptions about […]
Understanding Non-Parametric Post-Hoc Analysis When researchers need to compare the central tendencies of three or more independent groups, the standard approach is often the One-Way ANOVA. However, this parametric test relies on strict assumptions, notably that the data within each group are normally distributed and that the variances are homogeneous. When these assumptions are violated,
A Kruskal-Wallis test is used to determine whether or not there is a statistically significant difference between the medians of three or more independent groups. It is considered to be the non-parametric equivalent of the One-Way ANOVA. If the results of a Kruskal-Wallis test are statistically significant, then it’s appropriate to conduct Dunn’s Test to determine exactly which groups are