“Bayes’s moment has clearly arrived.” —The Wall Street Journal
A captivating and user-friendly tour of Bayes’s theorem and its global impact on modern life from the acclaimed science writer and author of The Rationalist’s Guide to the Galaxy.
At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything.
But who was the man who lent his name to this theorem? How did an 18th-century Presbyterian minister and amateur mathematician uncover a theorem that would affect fields as diverse as medicine, law, and artificial intelligence?
Fusing biography, razor-sharp science writing, and intellectual history, Everything Is Predictable is an entertaining tour of Bayes’s theorem and its impact on modern life, showing how a single compelling idea can have far reaching consequences.
Carrie –
I started this book with eagerness because, as a current masters student in data science, I wanted to know if taking a Bayesian statistics class in my future will be worth my time. After reading this book, I can confidently say it is. Tom Chivers is both informative and funny, something that is sorely needed with a dense topic that can become complex and convoluted very quickly. Chivers made a great effort to find interesting, and sometimes unusual, scenarios that Bayesian stats can be applied to, and I quite enjoyed that he recognized that the multiple use of math equations can quickly overwhelm his audience, so he used them sparingly while utilizing his voice to the utmost degree. I highly recommend this book for anyone interesting in prediction or bayesian statistics.
Mathematical Customer –
Never taking it off.
Larry K. –
Not overly mathematical for a book about a theorem. A great book that clears away a lot of fog about an important and timely subject.
Steve G –
I thoroughly enjoyed this book. I found the writing to be conversational and the explanations clear. Chivers made excellent use of analogies. The book could have lapsed into a treatise on math but it didn’t. The book maintained an even pacing, with frequent injections of subject-related humor. I also appreciated all the biographical information. Thank you to Netgalley and One Signal Publishers for the advance reader copy.
Stetson Thacker –
I strongly recommend this book. It is an accessible and engaging tour of Bayesian probability theory. The book balances conceptual exposition, breezy intellectual history, and practical applications. The meat of the work concerns two domains ripe for a Bayes’ revolution: research science and real-world decision-making/discourse. There is also a special coda about how the brain itself may be a Bayesian agent.
Steve –
Interesting read for people who like to understand probabilities and math principles without being a math whiz. I bought the book after viewing an interview of the author. He speaks rather hap hazardly and rambling in a random manner, but eventually makes an interesting point. So, I bought his book. The book reflects his speaking style with many anecdotal inserts. He does included much historical support and references to support his writings which I found very interesting.
Jaime –
This book is a great read. The topic is well explained and even entertaining, with many real-life examples. I would recommend it to anyone interested in an intuitive explanation of Bayes’ theorem.
However, the author occasionally interjects personal opinions on irrelevant matters (like his ability to perform well on tests or his ancestors) with sentences such as “If you are like me….” He also makes some comments that I found shocking about sensitive topics like race and eugenics. The author seems to be trying to justify the unjustifiable and uses the names of prominent figures, such as Bertrand Russell, to normalize these views. For instance, Russell is somehow equated with Dalton, who is known for his controversial theories on racial hierarchy.
While I agree with mentioning researchers working on the topics as a reference, the author places significant weight on authority, which he justifies through Bayes’ theorem. Although it might be “rational” to give more weight to well-known scientists, this approach contradicts the scientific method, which warns against placing individuals on a pedestal. Scientists, after all, are human.
These issues occur only in a few passages. Apart from that, the book is excellent. It is well-explained, easy to follow, and entertaining, featuring examples ranging from simple (coin flipping) to complex (human behavior). The book is also highly informative and motivated me to explore some of the research mentioned.