Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Dec 2023 · University of Chicago Press
Ebook
258
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About this ebook
“A delightful exposition of commonly-encountered statistical fallacies and paradoxes and why they matter.” —Samuel H. Preston, coauthor of Demography: Measuring and Modeling Population Processes
An essential guide to the ways data can improve decision making.
Statistics are everywhere: in news reports, at the doctor’s office, and in every sort of forecast, from the stock market to the weather. 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 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, drawing on cases from health campaigns, political movements, and more, shining a light on what we learn when we interpret data correctly, and what goes wrong when we don’t. 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.
“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
“[Downey’s] style is lively and designed to appeal to the curious reader.” —Choice
An essential guide to the ways data can improve decision making.
Statistics are everywhere: in news reports, at the doctor’s office, and in every sort of forecast, from the stock market to the weather. 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 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, drawing on cases from health campaigns, political movements, and more, shining a light on what we learn when we interpret data correctly, and what goes wrong when we don’t. 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.
“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
“[Downey’s] style is lively and designed to appeal to the curious reader.” —Choice
About the author
Allen B. Downey is a curriculum designer at the online learning company Brilliant and professor emeritus of computer science at Olin College. He is the author of Think Python, Think Bayes, and Think Stats, among other books. He writes about statistics and related topics on his blog, Probably Overthinking It.
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