Lesson 12: ANOVA

Overview Section

Here we'll introduce ANOVA (analysis of variance) using lm(), including the use of multiple predictors (multiple-way ANOVA), the assessment of interactions and the assessment of the residuals.


Upon completion of this lesson, you should be able to:

  • Fit ANOVA models using lm() and interpret the output using summary(), anova(), and TukeyHSD()
  • Assess model validity using diagnostic plots
  • Specify multiple predictors and their interactions
  • Calculate predicted values (group means) for complex models
  • Visualize interactions using interaction.plot()

The R code file and data files for this lesson can be found on the Essential R - Notes on learning R page.