Compared to a parametric test,Nonparametric tests use the information in the data more efficiently.

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Nonparametric tests make fewer assumptions about the underlying distribution of the data, which can be useful in certain situations where the assumptions of a parametric test are violated. However, this also means that nonparametric tests may be less powerful and may require larger sample sizes to detect differences between groups or variables. Therefore, parametric tests may actually use the information in the data more efficiently when the assumptions of the test are met.

Compared to a Parametric Test,Nonparametric Tests Use the Information in the Data