A. Jordan Nafa • Department of Political Science • University of North Texas
This github repository is home to the content for my Fall 2022 political
science research methods and causal inference course at the University
of North Texas. The class is taught from a primarily Bayesian
perspective using R, Stan, and
{brms} and focuses heavily on
reproducibility and application rather than math for math’s sake. This
repository will be updated throughout the course of the Fall 2022
semester with lecture materials, tutorials for R, and R scripts to
reproduce each of the articles listed on the course syllabus.
To download the current version of the course content, you can execute the following command from a desktop terminal
git clone --recursive https://github.com/ajnafa/psci-3300-political-science-research.git
Due to copyright limitations, PDF versions of the assigned readings for the course are not provided via github but are available upon request as is course content tailored to the Canvas LME (i.e., html pages for each week, screenshots of how I have the course’s Canvas page structured, etc.).
The content of this class relies in part on materials from courses designed by Andrew Heiss, Matthew Blackwell, and Thomas J. Leeper. I thank the authors for making their instructional materials publicly available. Acknowledgment here should not be construed as endorsement of any of the content or materials in this repository.
Text and figures: All text and images are licensed under Creative Commons (CC-BY-NC 4.0)
Code: All code is licensed under the BSD 3-Clause License.