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:
“Ask anyone committed to Marxist analysis how many angels on the head of a pin, and you will be asked in return to never mind the angels, tell me who controls the production of pins.”
—Joan Didion (b. 1934)
“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)