27/09/2025
đź“ŚNon-Parametric Tests are statistical methods used when your data doesn't meet the assumptions required for parametric tests (like a normal distribution).
📍Mann-Whitney U Test: Used to compare the distributions of two independent groups. It's the non-parametric alternative to the independent samples t-test. ​
📍Wilcoxon Signed-Rank Test: Used to compare two related groups or paired observations (like before-and-after measurements). It's the non-parametric alternative to the paired t-test. ​
📍Kruskal-Wallis H Test: Used to compare the distributions of three or more independent groups. It's the non-parametric alternative to a one-way ANOVA. ​
📍Friedman Test: Used to compare the distributions of three or more related groups (e.g., the same subjects measured under three different conditions). It's the non-parametric alternative to repeated measures ANOVA. ​
đź“ŤSpearman's Rank Correlation: Measures the association (strength and direction) between two ordinal variables (ranked data). It's the non-parametric alternative to the Pearson correlation.
📍 ​Chi-Square Test: Used to analyze categorical data (counts or frequencies). It can be used for tests of Goodness of Fit (comparing an observed distribution to an expected one) or Independence (seeing if there's a relationship between two categorical variables).
