On this page, I list a few open-source materials on math, statistics, and 'programming' for my students and whoever else comes across this. Some provide intuitive introductions, others more advanced content. Please note that none of these resources are my own, and all credit goes to the dedicated people behind these projects, who generously share their knowledge and didactic masterpieces with the public.

Please let me know should you encounter a broken link. Also, there is much more good stuff out there - if you know of a tool or a website that you found particularly helpful, please drop me a line!


Math refreshers:

• Check out the "Math for Political Scientists" course by J. Alexander Branham
• Khan Academy has some general video lessons on basic and advanced math
• Also specifically for political scientists, Havard offers a nice booklet covering basic and advanced mathematical content (as well as some R and LaTeX)
• David Siegel provides a comprehensive math camp with video explanations

Statistical theory:

• Seeing Theory provides visualisations of core statistical concepts. This is great for both learning and teaching
• Learning Statistics with R is a book project by Danielle Navarro, mainly directed at psychology students (but broadly applicable), and it is hard to overstate its usefulness as introductory textbook
• Lecture slides on "Advanced Quantitative Research Methodology" (various topics) by Gary King
• Comprehensive information and interactive materials on "The Fallacy of Placing Confidence in Confidence Intervals" by Richard D. Morey and others
• Some more resources for learning Bayesian on LearnBayes
• A visual explanation of Markov Chains by Victor Powell and Lewis Lehe
• Kevin Shoemaker has some great course materials leading up to Bayesian analysis
• Online access to a bit more advanced book on machine learning & supplementary materials by Hastie et al. (2009)

Learning R:

• If you are new to R and RStudio, follow these instructions on Swirl
• Essential R resources and further links are on Gary King's "Advanced Quantitative Research Methodology" website
• Under the heading "Teaching", Garrett Glasgow has many neat code chunks on basic and advanced topics
• For a steep learning curve, Kevin Shoemaker and Mitchell Gritts provide materials for an R bootcamp
• The primers on the RStudio Cloud provide for interactive learning of basics and the tidy dialect
• Andrew Heiss has a great course website for learning data visualization using ggplot
  
• A rich online resource listing many different & mostly free books on R, kicked off by Oscar Baruffa.
  

Learning Stata:

• Two good and easy-to-follow introductions to Stata are provided by Ista Zahn at Havard and Germán Rodríguez at Princeton
  *Disclaimer: while these two websites are publicly available, please note that Stata itself is not open source.

LaTeX materials:

• "The Not So Short Introduction to LaTeX" has pretty much everything you need to get started
• For a more interactive experience, you may also want to consider these Overleaf resources with this 30-minute intro
• Extensive documentation is offered by Wikibooks and by the Havard Mathematics Department

Finally, if you want to put your statistics skills to good use (beyond your research, of course), take a look at CorrelAid.