Hands-on computational modeling techniques for Bayesian analysis enable practical learning
Utilizes R and Stan for accessible and powerful statistical inference
Causal inference frameworks help users address causal questions in data analysis
Multilevel and hierarchical models provide tools for complex data structures
Statistical Rethinking 2nd Edition is a hardcover academic textbook designed for statisticians, data scientists, researchers, and graduate students. This resource serves as an introduction to applied Bayesian data analysis.
This edition provides computational modeling techniques utilizing R and Stan. It covers causal inference frameworks