Statistics + causal inference¶
Five ranked references. Rank 1 is the default spine, not a requirement to read all five.
1 | Causal Inference: What If¶
Miguel A. Hernán, James M. Robins | Causal primary spine | Graduate / advanced undergraduate
The most important rigorous bridge from observational data to intervention questions; defines targets, identification, bias, and causal estimation.
Amazon search | Full legal author PDF
2 | Regression and Other Stories¶
Andrew Gelman, Jennifer Hill, Aki Vehtari | Applied statistics spine | Undergraduate / graduate
Excellent model-building habits: regression, uncertainty, checking, transformations, and interpretation.
Amazon search | No legal full text located
3 | All of Statistics: A Concise Course in Statistical Inference¶
Larry Wasserman | Theory compact | Graduate / advanced undergraduate
Dense survey of estimation, testing, regression, Bayesian ideas, bootstrap, density estimation, and learning.
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4 | The Effect: An Introduction to Research Design and Causality¶
Nick Huntington-Klein | Open causal intuition | Undergraduate
Very strong bridge from identification ideas to real research designs; free web version remains legally available.
Amazon search | Full legal web edition
5 | Causal Inference: The Mixtape¶
Scott Cunningham | Empirical designs | Undergraduate / graduate
Hands-on treatment of DAGs, regression, matching, IV, diff-in-diff, RDD, and synthetic control.
Amazon search | Full legal web edition