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In the realm of statistical analysis, comparing multiple groups often relies on the familiar one-way analysis of variance (ANOVA). However, ANOVA thrives on the assumptions of normality and equal variances across groups. When these assumptions are violated, particularly when dealing with ordinal data (ranked or categorized data), the Friedman test emerges as a powerful non-parametric…

In the realm of statistical analysis, when comparing multiple groups, the familiar one-way analysis of variance (ANOVA) takes center stage. However, its effectiveness hinges on the assumption of normally distributed data and equal variances across groups. When these assumptions are violated, the Kruskal-Wallis test emerges as a non-parametric alternative, offering a robust and reliable method…

In the realm of statistical analysis, regression analysis serves as a cornerstone for exploring relationships between variables. However, the presence of extraneous variables, also known as covariates, can confound the observed relationships, leading to misleading interpretations. To address this challenge, analysis of covariance (ANCOVA) emerges as a powerful technique that allows us to control for…