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


Product Details

$24.00  $22.32
University of Chicago Press
Publish Date
6.32 X 9.23 X 0.62 inches | 1.05 pounds

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About the Author

Allen Downey is a Staff Producer at Brilliant and Professor Emeritus at Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and a Master's Degree from MIT.


"Downey's pure love for the subject shines through abundantly, as does his social conscience and belief in the importance of statistical methods to illuminate the greatest, most challenging issues of our time."--Aubrey Clayton, author of Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science
"Probably Overthinking It shows how fascinating and interesting statistics can be. Readers don't need to be expert mathematicians. They just need to bring their curiosity about the world."--Ravin Kumar, data scientist at Google
"Probably Overthinking It is a delightful exposition of commonly-encountered statistical fallacies and paradoxes and why they matter. The illustrations are powerful and the prose is exceptionally clear. There are few domains of human activity to which the lessons of this volume are not applicable."--Samuel H. Preston, coauthor of Demography: Measuring and Modeling Population Processes
"Mark Twain once observed that 'facts are stubborn things, but statistics are more pliable.' Downey understands just how that happens, even to people who are not trying to obfuscate. It was an honest researcher who in 1971 found data that seemed to indicate smoking by pregnant women might be good for their babies--a misinterpretation that may have delayed anti-smoking measures by a decade. In this clear and cogent analysis, Downey explains why the data was misunderstood, as well as much else. It is a valuable book."--Floyd Norris, Johns Hopkins University, former chief financial correspondent for the New York Times