There are two main types of inferential statistics: parametric and nonparametric. Parametric statistics are mathematical procedures for hypothesis testing, which assume that the distributions (set of scores) of the variables being evaluated have certain characteristics. For instance, analysis of variance (ANOVA) assumes that the underlying distributions are normally distributed and that the variances of the distributions being compared are similar. While parametric techniques are generally robust—that is, they have substantial power to detect differences or similarities even when the assumptions are violated—some distributions violate these assumptions so strikingly that nonparametric techniques ...

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