All of Statistics, by Larry Wasserman
Statistical Models, by David Freedman
Data Analysis Using Regression and Multilevel/Hierarchical Models, by Andrew Gelman and Jennifer Hill
Elements of Statistical Learning, by Hastie, Tibshirani, and Friedman.
Computer Age Statistical Inference, by Efron and Hastie.
An Introduction to Statistical Learning with Applications in R, by James, Witten, Hastie, and Tibshirani.
Bayesian Data Analysis, by Gelman, Carlin, Stern, Dunson, Vehtari, Rubin.
Statistics for Experimenters, by Box, Hunter, and Hunter.
Causal Inference for Statistics, Social, and Biomedical Sciences, by Imbens and Rubin.
A Guide to Econometrics, by Kennedy.
Mostly Harmless Econometrics, by Angrist and Pischke.
Theory of Point Estimation, by Lehmann and Casella.
Testing Statistical Hypotheses, by Lehmann and Romano.
“Statistical Modeling: The Two Cultures”, by Breiman.
“To Explain or to Predict?”, by Shmueli
“Prediction Policy Problems”, by Kleinberg, Ludwig, Mullainathan, and Obermeyer
“Machine Learning Methods for Causal Effects”, by Athey and Imbens