Most inferential statistics assume normal distributions.
Although these statistical tests work well even if the assumption of normality is violated, extreme deviations from normality can distort the results. I error rate. Although this may sound like a good thing, it often is accompanied by a substantial decrease in power. There is a collection of tests called distribution-free tests that do not make any assumptions about the distribution from which the numbers were sampled. Since alternative means of dealing with skewed distributions such as taking logarithms or square roots of the data are available, distribution-free tests have not achieved a high level of popularity.