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Parametric or non-parametric?

Parametric tests are more powerful when their assumptions hold, so they are the default worth trying. Non-parametric alternatives are the fallback when assumptions clearly fail, particularly with small samples or strongly skewed data. Neither is more rigorous in the abstract.

This comes up on Choosing the Right Statistical Test, where it is answered in the context of the work itself.

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