What is the difference between a parametric and a non-parametric test?
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Parametric tests: Assume the data follows a specific distribution (usually normal) and have parameters like mean and variance (e.g., t-tests, ANOVA).
Non-parametric tests: Do not assume a specific data distribution and are often used for ordinal data or when assumptions are violated (e.g., Mann-Whitney U test, Kruskal-Wallis test).