A work in progress. This module is being rebuilt to make econometrics more intuitive. Every lecture works with the same single data set, so students can apply each week’s method as they learn it, recreate the figures themselves, and build intuition and rules of thumb alongside the formal results. Some slides are still being written, and some figures are placeholders.
Ordinary least squares, taught thoroughly and in scalar algebra. Part 1 lays the statistical foundations. Part 2 fits and reads a simple regression. Part 3 adds controls, inference, functional form and dummy variables. Part 4 asks what happens when the assumptions behind it fail. These decks are mine rather than UCD’s: I built them independently, using the published module descriptor as a guide to the expected content. They are not the version UCD students are examined on.
Lectures
1. Foundations
Three lectures. Data, conditional means and sampling variation.
2. Simple Regression
Three lectures. Fitting a line, reading it, and how good it is.
3. Multiple Regression
Four lectures. Controls, inference, functional form and dummies.
4. Broken Assumptions
Two lectures. What happens when the assumptions fail.
Acknowledgements
Textbook
Jeffrey Wooldridge, Introductory Econometrics: A Modern Approach, is the set text, and the lectures follow its chapters on the simple and multiple regression models.
Using these. The slides are free to use, adapt and teach from. They are built in Quarto against my Dublin Beamer theme, so the source renders with no setup beyond Quarto and LaTeX. If you spot an error — and in twelve decks there will be some — tell me and I will fix it.