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)...

2-Proportions Test

The 2-Proportions Test is a test to check whether samples taken from two different conditions are different regarding their proportion. It compares whether the different proportions in two samples are different only due to random chance or because the samples have a...
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