Analysis of Variance Overviewsee also
Analysis of Variance OverviewAnalysis of variance (ANOVA) is similar to regression in that it is used to investigate and model the relationship between a response variable and one or more predictor variables. However, analysis of variance differs from regression in two ways: the predictor variables tend to be categorical. In effect, analysis of variance extends the two-sample t-test for testing the equality of two population means to a more general null hypothesis of comparing the equality of more than two means, versus them not all being equal. Several of Minitab's ANOVA procedures, however, allow models with both categorical and continuous variables.
Minitab's ANOVA capabilities include procedures for fitting ANOVA models to data collected from a number of different designs, for fitting MANOVA models to designs with multiple response, for fitting ANOM (analysis of means) models, and graphs for testing equal variances, for confidence interval plots, and graphs of main effects and interactions.