Chapter 9 Useful Internet Resources

9.1 Homepages

Quick-R has been a go-to reference when you look up simple examples for quite some time. It is a really helpful source.

This is a nice overview over all kinds of PolSci and IR data sets that are out there.

Data Science is fun! Why not starting your own project on a topic that catches your interest? You could share your insights as a homepage. Lillian Petersen could be a great inspiration.

The project Seeing Theory is a visually really beautiful and interactive take on what we are doing in this class. Note: The authors are undergrads from Brown University.

9.2 Online Books

Here is another good book that covers all we do in depth: Andrew Gelman, Jennifer Hill and Aki Vehtari (2020): “Regression and Other Stories”. You can download it here. (all legal…)

The LOST homepage is a bit of a repository for all kinds of models. It not only has code in R, but also a couple of other relevant statistical softwares, such as Julia or Python.

If you want to dig a little deeper on the causal aspects, you can check out this beautiful online book titled Causal Inference: The Mix Tape. Also available as a print version of course…

If you want to go even further down the causal path, this is another module at Mannheim University that also comes with a teaching homepage.

Interested in Data Visualization? This is a really great book on the topic from Jonathan Schwabish.

If you are keen to critically reflecting on what you are doing when you are analysing data, go and read Critical Thinking from Tom Chatfield. He also has a great video where he explains the core ideas.

Agresti, Alan. 2018. Statistical Methods for the Social Sciences. 5th ed. Pearson.
Fogarty, Brian. 2019. Quantitative Social Science Data With R. London: Sage.
Imai, Kosuke. 2018. Quantitative Social Science–an Introduction. Princeton University Press.