Links
Stats and Related Fields
Causal Inference
- Causal Inference: The Mixtape by Scott Cunningham
- The Effect: An Introduction to Research Design and Causality by Nick Huntington-Klein
- Causal Inference: What If by Miguel Hernán and James Robins
- Statistical Tools for Causal Inference by Sylvain Chabe-Ferret
- Applied Causal Inference Powered by ML and AI by Chernozhukov, Hansen, Kallus, Spindler, and Syrgkanis
- Even the Rich Can Make Themselves Poor: A Critical Examination of IV Methods in Marketing Applications by Peter Rossi (2014)
- Empirical Strategies in Economics: Illuminating the Path From Cause to Effect by Joshua Angrist (2022)
- Causality in Econometrics: Choice vs Chance by Guido Imbens (2022)
- Causality and Econometrics by James Heckman and Rodrigo Pinto (2022 working paper)
Bayesian Statistics
- Statistical Rethinking Course by Richard McElreath
- Statistical Rethinking 2 with rstan and the tidyverse by Solomon Kurz
- Bayesian Data Analysis by Gelman, Carlin, Stern, Dunson, Vehtari, and Rubin
- Bayesian Workflow by Gelman, Vehtari, Simpson, Margossian, Carpenter, Yao, Kennedy, Gabry, Bürkner, and Modrák
- Bayes Rules! An Introduction to Applied Bayesian Modeling by Alicia Johnson, Miles Ott, and Mine Dogucu
- Teaching Bayesian Statistics by TALMO
- Bayesian Data Analysis Course by Aki Vehtari
- Bayesian Statistics Readings by Andrew Heiss
Machine Learning
- Computer Age Statistical Inference by Bradley Efron and Trevor Hastie
- An Introduction to Statistical Learning by James, Witten, Hastie, and Tibshirani
- The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman
- Probabilistic Machine Learning by Kevin Murphy
- Applied Machine Learning for Tabular Data by Max Kuhn and Kjell Johnson
- Tidy Modeling with R by Max Kuhn and Julia Silge
Multilevel Models
- Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari
- Hierarchical Modeling Notes by Michael Betancourt
- Keep Calm and Learn Multilevel Logistic Modeling by Nicolas Sommet and Davide Morselli
Course Notes & Lecture Collections
- A Collection of Econometrics Resources by Giuseppe Cavaliere
- Math-Stat Course Notes by Joshua Tebbs
- Econometrics Notes by Tim Armstrong
- Notes by Adam N Smith
- Machine Learning Notes by Aric LaBarr
Data Science Practice & Communication
- Telling Stories with Data by Rohan Alexander
- The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists by Shan, Wang, Chen, and Song