This week focuses on the most common type of statistic model: the general linear model, which includes regression, ANOVA, ANCOVA, etc. as special cases. The learning goals for this week are: (1) an understanding of the structural components of a linear model, including continuous and categorical covariates, and interactions; (2) means of diagnosing and selecting among different models; (3) how to fit, summarize, diagnose linear models in R.
A very long set of slides, which covers material we will not be able to get to in class, are found here.
The script we will go through in class is found here. The data used in the script is found here.
