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
Famous quotes containing the words analysis and/or variance:
“A commodity appears at first sight an extremely obvious, trivial thing. But its analysis brings out that it is a very strange thing, abounding in metaphysical subtleties and theological niceties.”
—Karl Marx (1818–1883)
“There is an untroubled harmony in everything, a full consonance in nature; only in our illusory freedom do we feel at variance with it.”
—Fyodor Tyutchev (1803–1873)