Resources
Textbooks
The main text for the course is listed first. The remaining books are useful supplements. Each is available either as a free online version or in digital form via UW-Madison library access.
Main Texts
- Aronow, P. M., and Benjamin T. Miller. Foundations of Agnostic Statistics. Cambridge University Press, 2019.
Supplementary Texts
- Blackwell, Matthew. A User’s Guide to Statistical Inference and Regression.
- Blitzstein, Joseph K., and Jessica Hwang. Introduction to Probability. 2nd Edition. Chapman and Hall/CRC, 2019.
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.
- R: Download from https://www.r-project.org
- RStudio: Download from https://posit.co/download/rstudio-desktop/
- Positron: Download from https://positron.posit.co/
Recommended Guides for R Programming
The following are excellent introductions to R, roughly in increasing order of difficulty.
- R For Data Science Available at https://r4ds.hadley.nz/
- Data Visualization: A Practical Introduction Available at https://socviz.co/
- Advanced R Wickham, Hadley. Available at https://adv-r.hadley.nz/
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.
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.
- Quarto: Download from https://quarto.org/docs/get-started/
- Quarto Guide: https://quarto.org/docs/guide/
- Markdown Basics: https://quarto.org/docs/authoring/markdown-basics.html
- Note also the chapter on Quarto in R For Data Science
LaTeX Math Notation
Problem sets involve writing math, which you will typeset using LaTeX inside your Quarto document.
- Quarto math syntax: https://quarto.org/docs/authoring/markdown-basics.html#equations
- A quick LaTeX math reference: https://en.wikibooks.org/wiki/LaTeX/Mathematics
Math Review
The course assumes the algebra and single-variable calculus covered in the summer math camp. If you would like a refresher:
- Moore, Will H., and David A. Siegel. A Mathematics Course for Political and Social Research. Princeton University Press, 2013.
- Khan Academy calculus: https://www.khanacademy.org/math/calculus-1
- 3Blue1Brown, Essence of Calculus: https://www.3blue1brown.com/topics/calculus
Beyond the Course
- Models, Experiments and Data (MEAD) workshop: https://sites.google.com/view/meadwisc/home – the applied statistics workshop at UW-Madison. Attending is one of the best ways to see what quantitative political science actually looks like in practice, and you are strongly encouraged to come.
- Society for Political Methodology: https://polmeth.org/