Week 4 - 09/11

Date: Sep 11th - Sep 13th

What we will cover

In this session, we will talk about non-linear relations between our outcome and covariates, and how we can include polynomials to create a better fitting model. We will also start diving into Causal Inference: Potential outcomes framework, the fundamental problem of causal inference, causal estimands, and study design.

  • Angrist & Pischke. (2015). “Mastering Metrics”. Chapter 1: Randomized Trials. Pg. 1-11.

  • Marginal Revolution University. (2019). “Ceteris Paribus: Public vs. Private University”. Video materials from Mastering Metrics.

  • Grab N Go Info. (2022). “Average Treatment Effects ATE vs CATE vs ATT vs ATC | Causal Inference”.


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Download the R Script for the in-class exercise here:


Here is the full R script for this class, with some additional questions:


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