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analysis of variance
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collection of statistical models used to analyze the differences between group means and their associated procedures
Research
518,932 papers- Application of student's t-test, analysis of variance, and covariance.Annals of cardiac anaesthesia · 2019
- Analysis of variance.Circulation · 2008
- Likert scales, levels of measurement and the "laws" of statistics.Advances in health sciences education : theory and practice · 2010
- Analysis of variance of microarray data.Methods in enzymology · 2006
- Analysis of variance.Transfusion · 2018
via PubMed
Wikidata facts
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- Commons category
- Analysis of variance
- topic's main category
- Category:Analysis of variance
- described by source
- Armenian Soviet Encyclopedia
- Stack Exchange tag
- stats.stackexchange.com/tags/anova
- short name
- ANOVA
- maintained by WikiProject
- WikiProject Mathematics
Sources (2)
via Wikidata · CC0
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Encyclopedic overview
Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA compares the amount of variation between the group means to the amount of variation within each group. If the between-group variation is substantially larger than the within-group variation, it suggests that the group means are likely different. This comparison is done using an F-test. The underlying principle of ANOVA is based on the law of total variance, which states that the total variance in a dataset can be broken down into components attributable to different sources. In the case of ANOVA, these sources are the variation between groups and the variation within groups.
ANOVA was developed by the statistician Ronald Fisher. In its simplest form, it provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means.
Excerpted from Wikipedia’s “analysis of variance” article, available under the CC BY-SA 4.0 licence.