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How to Lie with Statistics Reissue Edition
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Over Half a Million Copies Sold--an Honest-to-Goodness Bestseller
Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to full rather than to inform.- ISBN-100393310728
- ISBN-13978-0393310726
- EditionReissue
- PublisherW. W. Norton & Company
- Publication dateOctober 17, 1993
- LanguageEnglish
- Dimensions5.5 x 0.4 x 8.3 inches
- Print length144 pages
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Editorial Reviews
Amazon.com Review
Although many of the examples used in the book are charmingly dated, the cautions are timeless. Statistics are rife with opportunities for misuse, from "gee-whiz graphs" that add nonexistent drama to trends, to "results" detached from their method and meaning, to statistics' ultimate bugaboo--faulty cause-and-effect reasoning. Huff's tone is tolerant and amused, but no-nonsense. Like a lecturing father, he expects you to learn something useful from the book, and start applying it every day. Never be a sucker again, he cries!
Even if you can't find a source of demonstrable bias, allow yourself some degree of skepticism about the results as long as there is a possibility of bias somewhere. There always is.
Read How to Lie with Statistics. Whether you encounter statistics at work, at school, or in advertising, you'll remember its simple lessons. Don't be terrorized by numbers, Huff implores. "The fact is that, despite its mathematical base, statistics is as much an art as it is a science." --Therese Littleton
Review
― New York Times
"A pleasantly subversive little book guaranteed to undermine your faith in the almighty statistic."
― Atlantic
About the Author
Product details
- Publisher : W. W. Norton & Company; Reissue edition (October 17, 1993)
- Language : English
- Paperback : 144 pages
- ISBN-10 : 0393310728
- ISBN-13 : 978-0393310726
- Item Weight : 6.2 ounces
- Dimensions : 5.5 x 0.4 x 8.3 inches
- Best Sellers Rank: #15,845 in Books (See Top 100 in Books)
- #4 in Business Statistics
- #6 in Statistics (Books)
- #12 in Probability & Statistics (Books)
- Customer Reviews:
About the authors

Darrell Huff (July 15, 1913 – June 27, 2001) was an American writer, and is best known as the author of How to Lie with Statistics (1954), the best-selling statistics book of the second half of the twentieth century.
Huff was born in Gowrie, Iowa, and educated at the University of Iowa, (BA 1938, MA 1939). Before turning to full-time writing in 1946, Huff served as editor of Better Homes and Gardens and Liberty magazine. As a freelancer, Huff produced hundreds of "How to" feature articles and wrote at least sixteen books, most of which concerned household projects. One of his biggest projects was a prize-winning home in Carmel-by-the-Sea, California, where he lived until his death.
Stanford historian Robert N. Proctor wrote that Huff "was paid to testify before Congress in the 1950s and then again in the 1960s, with the assigned task of ridiculing any notion of a cigarette-disease link. On March 22, 1965, Huff testified at hearings on cigarette labeling and advertising, accusing the recent Surgeon General's report of myriad failures and 'fallacies'."
First and foremost, though, Huff is credited with introducing statistics to a generation of college and high-school students on a level that was meaningful, available, and practical, while still managing to teach complex mathematical concepts. His most famous text, How to Lie with Statistics, is still being translated into new languages. His books have been published in over 22 languages, and continue to be used in classrooms the world over.
Bio from Wikipedia, the free encyclopedia.

Irving Geis (October 18, 1908 – July 22, 1997) was an American artist who worked closely with biologists. Geis's hand-drawn work depicts many structures of biological macromolecules, such as DNA and proteins, including the first crystal structure of sperm whale myoglobin.
Bio from Wikipedia, the free encyclopedia.
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This book was recommended to me in passing by one of my professors when I was completing the capstone course for my BS in mathematics. Largely because of who suggested it, I expected a book about mathematical statistics. Instead, this is a book about understanding how statistical analysis can be abused (by journalists, politicians, advertisers, etc., etc.). It does not denigrate the practice of statistical analysis itself (though you will not learn even a single technique from statistical theory in its 144 pages), but rather serves as a lighthearted cautionary tale about how easy it is to become convinced that statistics carry all the weight of science even though statistical analysis is both science and art.
The reader already well-versed in statistics will not find any new information but will still be pleased by the book's artful presentation of known ideas. Readers who are not so well-versed in statistics should consider this book required reading because it succinctly explains how the information we all consume every day may have been manipulated--intentionally or otherwise--to give us false impressions.
In fact, I would argue the value of this book has only increased in the decades since its initial publication. While the reader picking up this book upon its publication in 1954 would surely encounter plenty of statistics and graphs throughout the week, our modern 24-hour news cycle and constant immersion in a multimedia world has magnified the opportunity for statistical deception. Of course, you'll find that the book's examples are outdated (references to an exorbitant $25,000 salary for Yale graduates might seem at first more quaint than informative). However, despite the dated examples, the statistical phenomena described are as relevant as ever. Indeed, an argument could be made that the examples from yesteryear might even aid the book's pedagogical value by avoiding the contemporary issues that might cause the reader to don partisan intellectual blinders.
If I were to criticize, I would say that the book fails as an introduction to statistical thinking. For example, it rightly cautions the reader to beware of the difference between median and mean when interpreting reported "averages," but fails to provide much insight regarding when each of these measures of central tendency might be superior to the other. As such, the reader looking for insight regarding the practice of statistics, even from a non-technical perspective, may be disappointed. However, the reader interested in the consumption of statistical information will find a wealth of information packed into a charming little book.
Author Darrell Huff managed to create a wonderfully light and humorous read while still managing to convey a tremendous amount of information. This relatively short book is practically a quick introduction and handbook for many of the most common means of manipulating statistics. It is down-right amazing how many questionable practices you are able to spot after learning the content in this book. From tooth paste advertisements to election polls, the truly essential skills taught by this book help teach you how to dissect claims, and understand what is behind the marketing twists and biases.
One of the most wonderful aspects of this work, is the ability to convey a tremendous amount of information in a way that any laymen would be able to pick up and understand. The topics covered include: how sampling introduces bias, the various ways of reporting "averages" (mean, median, mode), how advertisers pick and choose among statistics, unreported probable error, manipulation of graphs, irrelevant data, and (of course) correlation vs. causation. One might go so far as to say that this handbook guide is an advertiser's worst nightmare, pointing out the many ways that numbers are used to convince us of incorrect conclusions.
While I certainly wasn't new to statistics, this book brought forth a breadth of information, presented in a fun, light-hearted way, and broken up with amusing illustrations. But, don't let its length or appearances fool you, the things you can learn are extraordinarily useful. I would highly recommend this book to a wide audience, anyone with a passing interest in how numbers are being used to deceive.
Great info! This is a classic book!
Top reviews from other countries
It really highlights that we can’t just accept data, especially in the public sphere.
Reviewed in Spain on October 23, 2022
107 pages and paperback. Should be sold for 250 max.
Book is dated and not relevant
Ok as a casual read but then its not value for the price.













