In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which 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 all equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing two, three, or more means.
Read more about Analysis Of Variance: Background and Terminology, Classes of Models, Assumptions of ANOVA, Characteristics of ANOVA, Logic of ANOVA, ANOVA For A Single Factor, ANOVA For Multiple Factors, Worked Numeric Examples, Associated Analysis, Study Designs and ANOVAs, ANOVA Cautions, Generalizations, History
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