Statistical & Hypothesis Tests: Using Non-parametric Tests & ANOVA Analysis

Two-sample T-tests are great for comparing population means given two samples. However if the number of samples increases beyond two we need a much more versatile and powerful technique – analysis of variance (ANOVA). Use this course to learn more about non-parametric tests and the ANOVA analysis. In this course youll explore the different use cases for Mann-Whitney U-tests the use of the non-parametric paired Wilcoxon signed-rank test and perform pairwise T-tests and ANOVA. Youll also get a chance to try your hand at the non-parametric variant of ANOVA – Kruskal Wallis test and post hoc tests such as Tukey’s honestly significant difference test (HSD). After completing this course you will be able to account for the effect of one or two independent categorical variables each having an arbitrary number of levels on a dependent variable using ANOVA.