Causal reasoning is at the core of everything we *see*, *do*, and
*imagine*. Causal inference is the foundation of scientific thinking and
reasoning. Every explicit decision we make is the realization of
causal thinking. You will be surprised to learn that the rigorous
study of causality as a science is relatively new in comparison to the
disciplines of statistics and probability. The history of the Causal
Revolution will surprise, inspire, entertain, and—at times—shock
you! Below is my 5-star Amazon review of the Judea Pearl’s
*The Book of Why: The New Science of Cause and Effect*
(which became an Amazon “Best Seller” within the first week of its release!).

“Wow! I am a physician epidemiologist with a doctorate in epidemiology
and I teach computational epidemiology (with R) at UC Berkeley. I had
the opportunity to study biostatistics from the best professors at UC
Berkeley School of Public Health (Steve Selvin, Nicolas Jewell,
Richard Brand, and many more). The field of causal inference was just
beginning to take off with biostatisticians piloting the plane (Mark
van der Laan, Nicolas Jewell, etc.). I avoided a rigorous study of
causal inference but eventually came around after studying Bayesian
networks (pioneered by Judea Pearl) for decision analysis. Judea
Pearl’s Bayesian networks and causal graphs connects the fields of
statistics, epidemiology, decision and computer sciences in a
profoundly elegant way. His work empowers and expands the potential of
“big data.” This is the first book written for the general public on
this topic. It will have a *huge impact*. Causality and causal
reasoning is at the core of everything we see, do, and imagine. He
provides a graphical tool (causal graphs) for encoding expert
knowledge (including community wisdom and experience). Anyone—yes,
anyone—can learn the basics. For additional rigor, there are
structural causal models (functional equations). I now consider it
“data scientific malpractice” to be designing studies, analyzing data,
and adjusting for confounders without using causal models. Human
brains are wired to resist new paradigms. Be intellectually wise and
humble and read this book–you will not regret it!”

## The Ladder of Causation

By the end of this book you will understand, appreciate, and value the “Ladder of Causation” (Figure below) as a way of thinking about decision making, causal reasoning, and causal discovery. You will develop a different appreciation of the important roles of epidemiology and statistics which have embraced the Causal Revolution.