[robwwilliams]

The battle between frequentist statisticians and those advocating Bayesian approaches is quite old—-back at least to Wright. Pearl is not inventing a dichotomy but explaining why models are necessary to evaluate causality. Is this genuine progress? Absolutely! Causal Bayesian modeling is transformative.

Every experimentalist and clinician will come away with good from Book of Why even if the tone rubs some the wrong way occasionally. I made this required reading in my human genetics course for grad students. Perfect level. Yes, I got some welcome pusback from bright students, but I know this book will have an indelible positive impact on their depth of thinking about data generation, model assumptions, confounders, interventions, and counterfactuals.