Non-parametric test

Non-parametric tests, also sometimes called distribution free tests, are a type of statistical test which is necessary to use when data does not have a probability distribution or does not have a distribution's parameters specified and known.  While technically non-parametric tests can be used on all kinds of data including even data with a normal distribution, usually parametric tests are preferred due to issues of statistical power.

Non-parametric tests include:

• Spearman’s rank correlation (similar to the Pearson's correlation)
• Kruskal-Wallis test (similar to the ANOVA )
• Wilcoxon signed-rank test (similar to the paired T test )
• Mann–Whitney–Wilcoxon test (similar to the two sample T test )
• Pearson's chi squared test