Nonparametric tests generally are more powerful than parametric tests when normality cannot be assumed.

Name: Nonparametric tests generally are more powerful than parametric tests when normality cannot be assumed.
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This is generally true, as nonparametric tests are designed to be robust to deviations from normality and do not rely on specific assumptions about the underlying distribution of the data. Therefore, they can often provide more accurate and reliable results when normality cannot be assumed.

Nonparametric Tests Generally Are More Powerful Than Parametric Tests When