变异数分析（Analysis of variance，简称ANOVA）为数据分析中常见的统计模型，主要为探讨连续型（Continuous）数据型态之因变量（Dependent variable）与类别型数据型态之自变量（Independent variable）的关系，当自变项的因子中包含等于或超过三个类别情况下，检定其各类别间平均数是否相等的统计模式，广义上可将T检定中变异数相等（Equality of variance）的合并T检定（Pooled T-test）视为是变异数分析的一种，基于T检定为分析两组平均数是否相等，并且采用相同的计算概念，而实际上当变异数分析套用在合并T检定的分析上时，产生的F值则会等于T检定的平方项。

Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences among group means and their associated procedures (such as "variation" among and between groups), developed by statistician and evolutionary biologist Ronald Fisher. In the ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are equal, and therefore generalizes the t-test to more than two groups. ANOVAs are useful for comparing (testing) three or more means (groups or variables) for statistical significance. It is conceptually similar to multiple two-sample t-tests, but is less conservative (results in less type I error) and is therefore suited to a wide range of practical problems.