The module covers the following topics: Introduction to correlation vs. causation; OLS and propensity score matching; introduction to dealing with unobservable characteristics; randomised controlled trials; instrumental variables; regression discontinuity design; difference-in-differences; static and dynamic linear panel data methods; introduction to maximum likelihood estimation; binary choice models; discrete choice models.

Descriptive statistics; Probability; Discrete random variables; Binomial and Poisson distributions; Bivariate distributions; covariance and correlation; Continuous random variables; uniform and normal distributions; Limit theorems; Sampling and sampling distributions; Hypothesis testing and confidence intervals; Non-parametric testing.

This module provides an introductory treatment of univariate and multivariate calculus, compounding and discounting, constrained optimization, and matrix algebra.