Cover image for The book of why : the new science of cause and effect / Judea Pearl and Dana Mackenzie.
The book of why : the new science of cause and effect / Judea Pearl and Dana Mackenzie.
Firest edition.
Publication Information:
New York : Basic Books, 2018.

Physical Description:
x, 418 pages ; 25 cm
Introduction: Mind over data -- The ladder of causation -- From buccaneers to guinea pigs: the genesis of causal inference -- From evidence to causes: Reverend Bayes meets Mr. Holmes -- Confounding and deconfounding: or, slaying the lurking variable -- The smoke-filled debate: clearing the air -- Paradoxes galore! -- Beyond adjustment: the conquest of Mt. Intervention -- Counterfactuals: mining worlds that could have been -- Mediation: the search for a mechanism -- Big data, artificial intelligence, and the big questions.
"Everyone has heard the claim, "Correlation does not imply causation." What might sound like a reasonable dictum metastasized in the twentieth century into one of science's biggest obstacles, as a legion of researchers became unwilling to make the claim that one thing could cause another. Even two decades ago, asking a statistician a question like "Was it the aspirin that stopped my headache?" would have been like asking if he believed in voodoo, or at best a topic for conversation at a cocktail party rather than a legitimate target of scientific inquiry. Scientists were allowed to posit only that the probability that one thing was associated with another. This all changed with Judea Pearl, whose work on causality was not just a victory for common sense, but a revolution in the study of the world"-- Provided by publisher.
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501 PEA Book Adult General Collection

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A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence
"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality--the study of cause and effect--on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why .

Author Notes

Judea Pearl is a Professor of Computer Science at UCLA. The author of three highly influential scholarly books, he is a winner of the Alan Turing Award, often considered the equivalent of the Nobel Prize for computer science. He is a member of the U.S. National Academy of Sciences, and was one of the first ten inductees into the IEEE Intelligent Systems Hall of Fame. He has received numerous awards and honorary doctorates, including the Rumelhart Prize (Cognitive Science Society), the Benjamin Franklin Medal (Franklin Institute) and the Lakatos Award (London School of Economics). He is the founder and president of the Daniel Pearl Foundation. He lives in Los Angeles, CA.
Dana Mackenzie is a Ph.D. mathematician turned science writer, and has written for such magazines as Science , New Scientist , Scientific American , Smithsonian , Nautilus , and Discover . His book, The Big Splat, or How Our Moon Came to Be, was named a Booklist Editors' Choice and selected as an Audiobook of the Year for 2010 by He received the 2012 Communication Award (Joint Policy Board for Mathematics) and the 2015 Chauvenet Prize for mathematical exposition (Mathematical Association of America). He lives in Santa Cruz, CA.

Table of Contents

Prefacep. ix
Introduction Mind over Datap. 1
Chapter 1 The Ladder of Causationp. 23
Chapter 2 From Buccaneers to Guinea Pigs: The Genesis of Causal Inferencep. 53
Chapter 3 From Evidence to Causes: Reverend Bayes Meets Mrp. 93
Chapter 4 Confounding and Deconfounding: Or, Slaying the Lurking Variablep. 135
Chapter 5 The Smoke-Filled Debate: Clearing the Airp. 167
Chapter 6 Paradoxes Galore!p. 189
Chapter 7 Beyond Adjustment: The Conquest of Mount Interventionp. 219
Chapter 8 Counterfactuals: Mining Worlds That Could Have Beenp. 259
Chapter 9 Mediation: The Search for a Mechanismp. 299
Chapter 10 Big Data, Artificial Intelligence, and the Big Questionsp. 349
Acknowledgmentsp. 371
Notesp. 373
Bibliographyp. 377
Indexp. 405