Wilcoxon test

The Wilcoxon test is a non-parametric statistical test used to compare two paired or independent samples to determine if their population mean ranks differ. Since it doesn’t assume that the data comes from a normal distribution, it’s useful when the normality assumption (required by parametric tests like the t-test) is violated.

There are two versions of the Wilcoxon test: Wilcoxon Signed-Rank Test: Used for paired data or matched samples. Wilcoxon Rank-Sum Test (also known as Mann-Whitney U test): Used for comparing two independent samples.

1. Wilcoxon Signed-Rank Test The Wilcoxon signed-rank test is used when you have paired data, such as measurements before and after a treatment on the same subjects, or matched pairs. It checks whether the median difference between the pairs is zero.

Null Hypothesis (H₀): The median difference between the pairs is zero. Alternative Hypothesis (H₁): The median difference is not zero (or, depending on the alternative hypothesis, it’s greater than or less than zero).

    Wilcoxon signed rank test with continuity correction

data:  number_of_speaking_languages and mean_exec_functions
V = 33, p-value = 0.2187
alternative hypothesis: true location shift is not equal to 0