Kruskal-Wallis Test: Non-Parametric Group Comparisons The Kruskal-Wallis Test is a widely used statistical method for comparing three or more independent groups when data does not meet the assumptions of parametric tests. It is the non-parametric counterpart to the one-way ANOVA, relying on rank-based analysis instead of raw data values. This article will discuss the purpose, […]
Mann-Whitney U Test: A Guide to Non-Parametric Analysis The Mann-Whitney U Test is a non-parametric statistical method used to compare two independent groups. It determines whether there is a significant difference in their distributions without assuming normality. This makes it an excellent alternative to the t-test for situations where data does not meet parametric test
Chi-square Test: Exploring Goodness-of-Fit and Independence The Chi-square test is one of the most widely used statistical methods for analyzing categorical data. It helps researchers evaluate whether observed data align with expected distributions or whether two categorical variables are associated. This test is versatile and essential for various fields, including social sciences, biology, and market
