Resources

Textbooks

These textbooks provide a number of the readings that will be used through the course of the semester. Each is available either as a free online version or in digital form via UW-Madison library access.

  • Cunningham, Scott. Causal inference: The Mixtape. Yale University Press, 2021.
  • Huntington-Klein, Nick. The Effect: An Introduction to Research Design and Causality. Chapman and Hall/CRC, 2021.
  • Hernán, Miguel A. and James M. Robins. Causal Inference: What If. Chapman & Hall/CRC. 2020.
  • Imbens, Guido W. and Donald B. Rubin. Causal Inference for Statistics, Social, and Biomedical Sciences. Cambridge University Press. 2015.
  • Morgan, Stephen L., and Christopher Winship. Counterfactuals and Causal Inference. Cambridge University Press, 2015.
  • Wager, Stefan. Causal inference: A statistical learning approach.

Software

R and RStudio

This course uses R for all programming assignments. You are welcome to use the RStudio Interactive Development Environment (IDE) to write code and edit the assignment write-up. Due to the extensive integration of Quarto into Posit-developed IDEs, I encourage using either RStudio or the more recent Positron IDE.

Quarto and Markdown

The assignments are distributed as .qmd Quarto files. Quarto is the successor to R Markdown and lets you present your analysis, code, figures and written discussion all in a single document. It uses Markdown syntax for formatting text and supports embedded R code chunks that execute when you render the document. This lets you present your analysis, code, figures, and written discussion all in one place.

To complete assignments, you will edit the provided .qmd file, adding your code and written responses, then render it to an HTML file for submission. Both your .html output and .qmd file will be submitted via Gradescope