Linear models for a quantitative response variable, with multiple categorical and/or quantitative predictors. Matrix formulation of linear regression. Model assessment and prediction.
By the end of the course, students are expected to be able to:
- Fit and interpret a linear regression model.
- Identify whether a linear regression model is appropriate for a given dataset.
- Critique a specific regression model applied to a given dataset on the basis of both diagnostic plots and hypothesis tests.
- Specify and interpret interaction terms and nonlinear terms.
- Faraway, Julian J. Linear Models with R, 2nd Edition. Chapman and Hall, 2014.
Note: information on this page is preliminary and subject to change.