Introduction to Econometrics
A companion text for ECON 103 · UCLA
A web-native companion text for ECON 103, UCLA’s introduction to econometrics. Adapted from the course lecture slides, with every figure rebuilt as reproducible R code.
Welcome
This is the companion text for ECON 103 — Introduction to Econometrics at UCLA (Summer Session C). It grew out of the course lecture slides and is meant to be read alongside them: the slides are the in-class sketch; this book is the worked-out, re-readable version you can return to while doing problem sets.
Econometrics is the set of tools economists use to learn about the world from data — to move from “these two things seem related” to “a one-unit change in \(X\) is associated with a \(\beta\)-unit change in \(Y\), and here is how sure we are.” We build that toolkit from the ground up:
- Part I — Probability Foundations develops the language of uncertainty: random variables, expectation and variance, the Normal distribution, and the Central Limit Theorem.
- Part II — Simple Linear Regression introduces the workhorse model \(Y_i = \beta_1 + \beta_2 X_i + e_i\): how we estimate it, what makes the estimates trustworthy, and how to do inference (confidence intervals and hypothesis tests).
- Part III — Multiple Regression extends everything to many regressors, then puts it to work: interactions, \(F\)-tests, model specification, dummy variables, and a first look at causal inference and treatment effects.
Lecture slides & practice
Each lecture pairs with a book chapter. The table below links the chapter (click the topic), a set of practice questions, and the in-class slide deck.
| Lecture | Practice | Slides |
|---|---|---|
| 1 · What Is Econometrics? |
Part I — Probability Foundations
Part II — Simple Linear Regression
Part III — Multiple Regression
How to use this book
Throughout, bold dark-blue marks a term the first time it appears, and shaded boxes flag the three things worth pausing on:
- a Definition — the precise meaning of a term;
- a Property — a fact or rule you can rely on;
- an Example — the idea worked through on numbers.
Every figure in this book is generated from R code. By default the code is hidden so the text reads cleanly, but you can click “Show the R code” above any figure to see exactly how it was made — and copy it into your own session. The course uses R throughout the labs, so treating the figures as runnable examples is part of the point.
Acknowledgements
The course follows Hill, Griffiths & Lim, Principles of Econometrics (5th ed.) (Hill, Griffiths, and Lim 2018), with cross-references to Stock & Watson, Introduction to Econometrics (4th ed.) (Stock and Watson 2019). The lab materials build on earlier versions of ECON 103 taught by colleagues at UCLA.
This book is under active construction during Summer 2026. Part I is being published chapter by chapter; later parts will follow as the term progresses.