Nonparametric tests are preferred to parametric tests since they are always more powerful.

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Nonparametric tests are not always more powerful than parametric tests. The choice between the two types of tests depends on the specific characteristics of the data and the research question at hand. Parametric tests may be more powerful when the underlying assumptions are met and the data follows a normal distribution. Nonparametric tests are more appropriate when there are violations of the assumptions or when the data is not normally distributed.

Nonparametric Tests Are Preferred to Parametric Tests Since They Are