For testing if 3 or more variables have identical population means, our first option is a repeated measures ANOVA. This requires our data to meet some assumptions -like normally distributed variables. If such assumptions aren’t met, then our second option is the Friedman test: a nonparametric alternative for a repeated-measures ANOVA. Strictly, the Friedman test can […]
For comparing two metric variables measured on one group of cases, our first choice is the paired-samples t-test. This requires the difference scores to be normally distributed in our population. If this assumption isn’t met, we can use Wilcoxon S-R test instead. It can also be used on ordinal variables -although ties may be a real issue for Likert items. […]
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