When the data are normally distributed, using nonparametric tests may be an overly conservative strategy that makes it difficult to detect effects.

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Nonparametric tests are designed to be used when the assumptions of parametric tests, such as normality, are violated. Therefore, when the data are normally distributed, using nonparametric tests can be overly conservative and may decrease the power to detect effects. In such cases, it is better to use parametric tests.

When the Data Are Normally Distributed, Using Nonparametric Tests May