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Additional testing and analysis
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. ANOVAs are helpful because they possess an advantage over a two-sample t-test. 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.

See also

ANOVA on ranks
ANOVA-simultaneous component analysis
Design of experiments
Duncan’s new multiple range test
Explained variance and unexplained variance
iedman test
Kruskal–Wallis test
List of important publications in statistics
Measurement uncertainty
Multiple comparisons
Squared deviations
Tukey’s test of additivity

From Wikipedia, the free encyclopedia : Additional testing and analysis
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