Jump to ratings and reviews
Rate this book

Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions

Rate this book
An essential guide to the ways data can improve decision making. Statistics are in news reports, at the doctor’s office, and in every sort of forecast, from the stock market to the weather. Blogger, teacher, and computer scientist Allen B. Downey knows well that people have an innate ability both to understand statistics and to be fooled by them. As he makes clear in this accessible introduction to statistical thinking, the stakes are big. Simple misunderstandings have led to incorrect medical prognoses, underestimated the likelihood of large earthquakes, hindered social justice efforts, and resulted in dubious policy decisions. There are right and wrong ways to look at numbers, and Downey will help you see which are which. Probably Overthinking It uses real data to delve into real examples with real consequences, drawing on cases from health campaigns, political movements, chess rankings, and more. He lays out common pitfalls—like the base rate fallacy, length-biased sampling, and Simpson’s paradox—and shines a light on what we learn when we interpret data correctly, and what goes wrong when we don’t. Using data visualizations instead of equations, he builds understanding from the basics to help you recognize errors, whether in your own thinking or in media reports. Even if you have never studied statistics—or if you have and forgot everything you learned—this book will offer new insight into the methods and measurements that help us understand the world.

258 pages, Kindle Edition

Published May 31, 2024

35 people are currently reading
19 people want to read

About the author

Allen B. Downey

36 books237 followers
Allen Downey is a Professor Emeritus at Olin College and the author of a series of freetextbooks related to software and data science, including Think Python, Think Bayes, and Think Complexity, which are also published by O’Reilly Media. His blog, Probably Overthinking It, features articles on Bayesian probability and statistics. He holds a Ph.D. in computer science from U.C. Berkeley, and M.S. and B.S. degrees from MIT.

Ratings & Reviews

What do you think?
Rate this book

Friends & Following

Create a free account to discover what your friends think of this book!

Community Reviews

5 stars
4 (57%)
4 stars
3 (42%)
3 stars
0 (0%)
2 stars
0 (0%)
1 star
0 (0%)
Displaying 1 of 1 review
Displaying 1 of 1 review

Can't find what you're looking for?

Get help and learn more about the design.