Flaws and Fallacies in Statistical Thinking

by Stephen Kent Campbell

This book was written with a dual first, the author was motivated to relieve his distress over the faulty conclusions drawn from the frequent misuse of relatively simple statistical tools such as percents, graphs, and averages. Second, his objective was to create a nontechnical book that would help people make better-informed decisions by increasing their ability to judge the quality of statistical evidence. This volume achieves both, serving as a supplemental text for students taking their first course in statistics, and as a self-help guide for anyone wishing to evaluate statistical evidence more judiciously.
The sequence of topics corresponds with that of many beginning textbooks in statistics, and the terminology and treatment of subjects are based on the assumption that readers have had little or no prior exposure to statistics or formal mathematics. The author examines the perils of statistical ignorance, some problems in basic measurement and definition, and the prevalence of meaningless statistics, far-fetched estimates, cheating charts, and accommodating averages. He explains common pitfalls of statistical thinking such as ignoring dispersion, inflating percentages, drawing improper comparisons, jumping to conclusions, and making errors of probability and induction. Playful in tone but scrupulously accurate in nature, this text is equally valuable in and out of the classroom.

Genres: Nonfiction, Science, Mathematics

208 pages, Paperback

First published October 1, 1973

Reviews

[Lisa Vegan · Rating 4 out of 5]

I read and own a 1974 edition of this book so I don’t know what changes, if any, are in this 2004 edition. This book, more than any other, taught me to think critically when presented with “statistics” about anything. When I hear any statistic quoted, I now ask how they came to the conclusion they did, always questioning the validity of any study. And it was an enjoyable book to read, not dry at all. Plenty of humor and an accessible style, but gives tons of good information about how to evaluate incoming information. Also recommended: How to Lie with Statistics by Darrell Huff.