Two-way analysis of variance: Difference between revisions

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{{expert needed|statistics |date=January 2012}}

In [[statistics]], the '''two-way [[analysis of variance]]''' ('''ANOVA)''') is an extension of the [[One-way analysis of variance|one-way ANOVA]] that examines the influence of two different [[Categorical variable|categorical]] [[independent variables]] on one [[Continuous function|continuous]] [[dependent variable]]. The two-way ANOVA not only aims at assessing the [[main effect]] of each independent variable but also if there is any [[Interaction (statistics)|interaction]] between them.

==History==

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==See also==

* [[Analysis of variance]]

* [[F test]] (''Includes a one-way ANOVA example'')

* [[Mixed model]]

* [[Multivariate analysis of variance|Multivariate analysis of variance (MANOVA)]]

* [[One-way ANOVA]]

* [[F test]] (''Includes a one-way ANOVA example'')

* [[Repeated measures#Repeated measures ANOVA|Repeated measures ANOVA]]

* [[Multivariate analysis of variance|Multivariate analysis of variance (MANOVA)]]

* [[Tukey's test of additivity]]

* [[Mixed model]]

==Notes==

{{Reflist}}

== References ==

* {{cite book |author=[[George Casella]] |date=18 April 2008 |title=Statistical design |url=https://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-75964-7 |publisher=[[Springer Science+Business Media|Springer]] |isbn=978-0-387-75965-4 }}

==Notes==

{{Reflist}}

[[Category:Analysis of variance]]