A non-parametric test should be pursued if there is reason to believe that the distributional assumptions of the corresponding parametric test have been violated to the extent that the parametric test is not robust.

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A non-parametric test is a good alternative when the assumptions of normality, homogeneity of variance, or linearity are not met in the data. Non-parametric tests do not rely on specific distributional assumptions and are generally considered more robust than parametric tests.

A Non-Parametric Test Should Be Pursued If There Is Reason