12. Linear Regression I¶
This is the first 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, in general, the rationale behind parametric statistical models;
fit and interpret a linear regression model;
describe the main properties of ordinary least squares estimators;
explain confidence intervals and hypothesis testing for regression coefficients
Acknowledgements: Thank you to Jennifer Nicholas and Chris Frost whose notes on linear regression were particularly useful in the development of the current lesson.