Hi, in this video I explain the difference between parametric and non-parametric tests! You want to calculate a hypothesis test, but don't know exactly what the difference is between a parametric and non-parametric test and are wondering when to use which test. If you want to calculate a hypothesis test, you must first check the assumptions for the respective hypothesis test. One of the most common assumption is that the data used must be normally distributed. Put simply, if your data is normally distributed, parametric tests are used, e.g. the t-test, analysis of variance or pearson correlation. If your data is not normally distributed, non-parametric tests are used, e.g. the Mann-Whitney U test or the Spearman correlation.
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0:00 What are parametric and non-parametric hypothesis tests?
1:54 Pearson correlation vs. the Spearman correlation
4:00 t-test for independent samples vs. Mann Whitney U test
5:43 List of parametric and non-parametric hypothesis tests.
6:17 Calculating parametric and non-parametric hypothesis tests with DATAtab