Permutation tests are a type of non-parametric statistical test that evaluate the significance of an observed effect by comparing it to the distribution of effects generated by randomly rearranging the data. This approach allows researchers to assess whether the observed results are statistically significant without relying on traditional assumptions about the data, such as normality or homogeneity of variance. By using permutation tests, one can accurately determine the likelihood of observing the given effect under the null hypothesis, especially in complex analyses like dimensionality reduction techniques.
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