Statistics is a difficult topic. I recommend learning from multiple sources. My recommendations here lean a bit toward econometrics as I believe their approaches are the most applicable to common problems in our discipline. For studying unobservable properties of individuals (e.g., self-control, differential association, moral anomie), however, you’ll want to look to social psychology (i.e., psychometrics) and latent variable models (e.g., structural equation modeling).
Recommended Textbooks
By level of difficulty and complexity of maths:
- Low:
- The two textbooks for this course!
- OpenIntro Statistics by Diez et al. A free and open source introduction general statistics suitable for pretty much anyone.
- OpenIntro Introduction to Modern Statistics by Cetinkaya-Rundel et al. A free and open source stats introduction emphasizing R programming. Still suitable for pretty much anyone. Has interactive R tutorials.
- Medium-Low:
- Data Analysis Using Regression and Multilevel/Hierarchical Models by Gelman & Hill. A classic introduction and reference for multilevel models. Comprehensive.
- Statistical Rethinking by McElreath. A course in bayesian stats that made a big impact on making these methods accessible.
- Counterfactuals and Causal Inference by Morgan & Winship. Classic introduction to causal inference for social scientists. Accessible yet one of the best desktop references.
- Introductory Econometrics: A Modern Approach by Wooldridge. One of the most used introductory textbooks in public policy and sociology. Rigorous but accessible.
- Medium-High:
- Hierarchical Linear Models by Raudenbush & Bryk. The canonical reference for hierarchical models.
- Econometric Analysis of Cross Section and Panel Data by Wooldridge. The canonical reference for econometrics. Covers nearly everything and in depth.
- High:
- Statistical Inference by Casella & Berger. Often seen as the best first year textbook for statistics graduate students. Deep coverage of fundamentals.
Assorted Resources
- Library of Statistical Techniques curated by Nick Huntington-Klein.
- Common statistical tests are linear models by Jonas Lindeløv