Permutation Test
A resampling-based test that evaluates whether an observed difference could be due to chance with weaker reliance on distributional assumptions.
Permutation tests offer a valuable alternative when classical parametric assumptions are weak or questionable. The core idea is to repeatedly shuffle group labels and evaluate whether the observed difference could plausibly arise by chance. This provides an empirical testing framework without relying too heavily on theoretical distributions. It is especially powerful in small-data settings, with complex metrics, or when standard assumptions are violated. Permutation tests use the data itself as the reference for judging the reliability of the result.
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