has part is about has_specified_input has_specified_output achieves_planned_objective data set population statistical hypothesis test objective study design independent variable study design dependent variable data transformation false positive rate polychotomous variable Kruskal Wallis test 1 1 2 1 H test Orlaith Burke Alejandra Gonzalez-Beltran Philippe Rocca-Serra The Kruskal–Wallis test is a null hypothesis statistical testing objective which allows multiple (n>=2) groups (or conditions or treatments) to be compared, without making the assumption that values are normally distributed. The Kruskal–Wallis test is the non-parametric equivalent of the independent samples ANOVA. The Kruskal–Wallis test is most commonly used when there is one nominal variable and one measurement variable, and the measurement variable does not meet the normality assumption of an anova. http://udel.edu/~mcdonald/statkruskalwallis.html kruskal.test() http://stat.ethz.ch/R-manual/R-patched/library/stats/html/kruskal.test.html rank-sum test for the comparison of multiple (more than 2) samples. scipy.stats.mstats.kruskalwallis(*args) http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.mstats.kruskalwallis.html source code: https://github.com/scipy/scipy/blob/v0.15.1/scipy/stats/mstats_basic.py#L800 ranking non-parametric test continuous variable between group comparison objective p-value pending final vetting