13. Linear Regression II¶
This is the second of three sessions that explore linear regression modelling. These are models where the outcome of interest is a continuous variable.
Intended learning outcomes
By the end of this session, you will be able to:
explain the difference between a univariable and multivariable linear regression model
fit and interpret a multivariable linear regression
describe the principles of centering
interpret categorical variables, quadratic terms and interaction terms included in a linear regression model
Acknowledgements: Thank you to Jennifer Nicholas and Chris Frost whose notes on linear regression were particularly useful in the development of the current lesson.