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.