Editing Analysis of variance (section)

{{short description|Collection of statistical models}}
{{Use dmy dates|date=March 2020}}

'''Analysis of variance (ANOVA)''' is a family of [[statistical methods]] used to compare the [[Mean|means]] of two or more groups by analyzing variance. Specifically, ANOVA compares the amount of variation ''between'' the group means to the amount of variation ''within'' each group. If the between-group variation is substantially larger than the within-group variation, it suggests that the group means are likely different. This comparison is done using an [[F-test]]. The underlying principle of ANOVA is based on the [[law of total variance]], which states that the total variance in a dataset can be broken down into components attributable to different sources. In the case of ANOVA, these sources are the variation between groups and the variation within groups. 

ANOVA was developed by the [[statistician]] [[Ronald Fisher]]. In its simplest form, it provides a [[statistical test]] of whether two or more population [[mean]]s are equal, and therefore generalizes the [[Student's t-test#Independent two-sample t-test|''t''-test]] beyond two means.
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