Nonparametric test

Nonparametric tests imply that there is no assumption of a specific distribution (whereas the so-called parametric Hypothesis Tests as t-Test, ANOVA, etc., assume that the data are a sample from the normal distribution).

Kruskal-Wallis Test

The Kruskal-Wallis test is a nonparametric test comparing the medians of independent random samples from two or more populations. It works when the Y variable is continuous, discrete-ordinal, or discrete-count, and the X variable is discrete with two or more...


The F-Test is a test for equal variances comparing the variations of two groups when the distributions are normal (X in two groups only).

Analysis of Variance (ANOVA)

ANOVA is a hypothesis test to check whether the average differences between groups are significant or only due to random chance. It works when the Y variable is continuous and the X variable is discrete. Practitioner’s Tip: The name ANOVA (ANalysis Of VAriances)...