What is "analysis of variance"

Analysis of variance \A*nal"y*sis of variance\, n. (Statistics) a statistical technique by which the results of an observation or experiment are analyzed to determine the relative contributions of the different possible causative factors or variables to the outcome. Abbreviated ANOVA.

n. (context statistics English) A collection of statistical models, and their associated procedures, in which the observed variance is partitioned into components due to different explanatory variables.

n. a statistical method for making simultaneous comparisons between two or more means; a statistical method that yields values that can be tested to determine whether a significant relation exists between variables [syn: ANOVA]

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 more conservative (results in less type I error) and is therefore suited to a wide range of practical problems.