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.
Objectives
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.