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Whereas one-way analysis of variance (ANOVA) tests measure significant effects of one factor only, two-way analysis of variance (ANOVA) tests (also called two-factor analysis of variance) measure the effects of two factors simultaneously. For example, an experiment might be defined by two parameters, such as treatment and time point. One-way ANOVA tests would be able to assess only the treatment effect or the time effect. Two-way ANOVA on the other hand would not only be able to assess both time and treatment in the same test, but also whether there is an interaction between the parameters. A two-way test generates three p-values, one for each parameter independently, and one measuring the interaction between the two parameters.
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