A parametric test is a statistical test that assumes the data follows a specific distribution or has certain parameters. It is used when certain assumptions about the data can be made.
Think of a parametric test as using a specific recipe to bake a cake. You assume that you have all the necessary ingredients and follow the instructions precisely, resulting in an expected outcome.
Nonparametric Test: A nonparametric test is a statistical test that does not make any assumptions about the underlying distribution of the data.
Hypothesis Testing: Hypothesis testing is a statistical method used to make inferences or draw conclusions about population parameters based on sample data.
Central Limit Theorem: The central limit theorem states that regardless of the shape of the population distribution, with sufficiently large sample sizes, the sampling distribution of means will be approximately normally distributed.
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