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

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When parametric assumptions are met, researchers are in greater danger of making a Type I error with a parametric test than with a nonparametric test. Nonparametric tests are generally more conservative and have less power than parametric tests, but they do not rely on as many assumptions about the distribution of the population from which the sample was drawn.

When Parametric Assumptions Are Met, Researchers Are in Greater Danger