When parametric assumptions are met, researchers are in greater danger of making a Type II error with a nonparametric test than with a parametric test.

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Nonparametric tests are generally less powerful than parametric tests when the assumptions of the parametric tests are met, meaning they are more likely to fail to reject a false null hypothesis, leading to a higher risk of a Type II error.

When Parametric Assumptions Are Met, Researchers Are in Greater Danger