# Stat-Spotting: A Field Guide to Identifying Dubious Data

## Synopsis

Does a young person commit suicide every thirteen minutes in the United States? Are four million women really battered to death by their husbands or boyfriends each year? Is methamphetamine our number one drug problem today? Alarming statistics bombard our daily lives, appearing in the news, on the Web, seemingly everywhere. But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading.

This new edition contains revised benchmark statistics, updated resources, and a new section on the rhetorical uses of statistics, complete with new problems to be spotted and new examples illustrating those problems. Joel Best's best seller exposes questionable uses of statistics and guides the reader toward becoming a more critical, savvy consumer of news, information, and data.

Entertaining, informative, and concise, Stat-Spotting takes a commonsense approach to understanding data and doesn't require advanced math or statistics.

## Excerpt

I was introduced to thinking about bad statistics when I read Darrell Huff’s How to Lie with Statistics as a first-year college student. By the time I checked out the library’s copy, that book was more than ten years old, and the volume showed a lot of wear. Huff’s examples no longer seemed current, and I particularly remember that the graphs he reproduced from newspaper articles struck me as somehow old-fashioned. Nonetheless, that book made a bigger impression on me than anything else I read during my first year in college. I understood that, even if the book’s examples were no longer timely, Huff’s lessons were timeless. As the years went by, I found myself recalling How to Lie with Statistics when I encountered dubious numbers in my reading. I discovered that people continued to get confused by statistics in the same ways Huff had identified.

Updating Stat-Spotting has forced me to think about what’s timely and what’s timeless. This book offers a catalog of common problems that can be found in statistics, particularly the sorts of numbers that pop up when people are debating social issues. These problems—the errors in reasoning people make when they . . .

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