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ANOVA / MANOVA PDF Print E-mail
The purpose of analysis of variance is to test differences in means for statistical significance. This is accomplished by analyzing the variance, that is, by partitioning the total variance into the component that is due to true random error and the components that are due to differences between means. These latter variance components are then tested for statistical significance, and, if significant, we reject the null hypothesis of no differences between means and accept the alternative hypothesis that the means are different from each other.

In practice, there are several types of ANOVA depending on the number of treatments and the way they are applied to the subjects in the experiment. Designs include:
 
Basic Designs
  • Single-Factor ANOVA
  • Multi-Factor ANOVA
Complex Designs
  • Between-Groups and Repeated Measures
  • Incomplete (Nested) Designs
Analysis of Covariance (ANCOVA)
  • Fixed Covariates
  • Changing Covariates
Multivariate Designs: MANOVA/MANCOVA
  • Between-Groups Designs
  • Repeated Measures Designs