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todays topic is about parametric and non-parametric tests and lets get started why are you interested in this topic you want to calculate a hypothesis test but you dont know exactly what the difference is between a parametric and a non-parametric test and youre wondering when to use which test if you want to calculate a hypothesis test you must first check the assumptions one of the most common assumptions is that the data used must show a certain distribution usually the normal distribution simplified we could say that if your data is normally distributed parametric tests are used for example the t test the anova or a pearson correlation if your data is not normally distributed you use a non-parametric test for example a man with new test or a spearman correlation what about the other assumptions of course you still have to check if there are further assumptions for the respective test but in general there are less assumptions for non-parametric tests than for parametric tests so