How to Lie with Statistics Reissue Edition

by Darrell Huff (Author), Irving Geis (Illustrator)

394 customer reviews

ISBN-13: 978-0393310726

ISBN-10: 0393310728

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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.

How to Lie with Statistics

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Editorial Reviews

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"There is terror in numbers," writes Darrell Huff in How to Lie with Statistics. And nowhere does this terror translate to blind acceptance of authority more than in the slippery world of averages, correlations, graphs, and trends. Huff sought to break through "the daze that follows the collision of statistics with the human mind" with this slim volume, first published in 1954. The book remains relevant as a wake-up call for people unaccustomed to examining the endless flow of numbers pouring from Wall Street, Madison Avenue, and everywhere else someone has an axe to grind, a point to prove, or a product to sell. "The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify," warns Huff.

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

“A hilarious exploration of mathematical mendacity…. Every time you pick it up, what happens? Bang goes another illusion!” (The New York Times)

“In one short take after another, Huff picks apart the ways in which marketers use statistics, charts, graphics and other ways of presenting numbers to baffle and trick the public. The chapter “How to Talk Back to a Statistic” is a brilliant step-by-step guide to figuring out how someone is trying to deceive you with data.” (Wall Street Journal)

“Illustrator and author pool their considerable talents to provide light lively reading and cartoon far which will entertain, really inform, and take the wind out of many an overblown statistical sail.” (Library Journal)

“A pleasantly subversive little book, guaranteed to undermine your faith in the almighty statistic.” (Atlantic)

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Product Details

Paperback: 144 pages
Publisher: W. W. Norton & Company; Reissue edition (October 17, 1993)
Language: English
ISBN-10: 0393310728
ISBN-13: 978-0393310726
Product Dimensions: 5.5 x 0.4 x 8.2 inches
Shipping Weight: 7.2 ounces (View shipping rates and policies)
Average Customer Review: 4.4 out of 5 stars See all reviews (394 customer reviews)
Amazon Best Sellers Rank: #10,013 in Books (See Top 100 in Books)
- #5 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics
- #6 in Books > Business & Money > Education & Reference > Statistics
- #8 in Books > Science & Math > Mathematics > Applied > Probability & Statistics

Customer Reviews

394

4.4 out of 5 stars

5 star		66%
4 star		21%
3 star		8%
2 star		3%
1 star		2%

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Top Customer Reviews

Statistics don't lie; people do.

By Mary P. Campbell on July 3, 2001

Format: Paperback

This book, written in 1954, is just as pertinent today (perhaps even more so, as it's so easy to acquire statistics due to our current technology) -- Darrell Huff gives people the tools to talk back to statistics. Though there is a little bit about deliberate deception, in such things as "The Gee-Whiz Graph" (about how the graphical display of statistics can be twisted so that one can get any desired result, though the stats aren't changed), the meat of the book is regarding sound statistical reasoning, something that people today really need to consider.
For example, every person who listens to the latest survey showing a correlation between certain food and certain health problems or benefits should read "Post Hoc Rides Again", in which people erroneously leap from statistical correlation to a cause-and-effect relationship. An example given in the book is a report in which it was found that smokers had lower grades in college; ergo, said the researcher, smokers wishing to improve their grades should quit smoking! Of course, a statistical study showing that there's a "significant" relation between smoking and low grades doesn't show which causes the other -- perhaps educational failure draws people to smoke! My own theory would be that the =type= of person who is given to smoking is also given to not doing well in school; instead of cause and effect, one has a correlation from a shared, third (and unnamed) cause. One comes across these fallacies in the news =every=day=; I've been reading my online news, and in the science section I've already found two suspicious cause-and-effect reports. As Huff notes, it's not the statistics which are in question -- it's how they're used.Read more ›

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By Michael R. Chernick on February 12, 2008

Format: Paperback

Statisticians hate the old adage "Lies, Damned Lies and Statistics", but statistical methods do have that reputation with the general public. There are many excellent accounts, some even understandable to laymen that explain the proper ways to analyze, study and report the analysis of statistical data. Huff's famous account is illustrative and well written. It gives the average guy a look at how statistics is commonly misused (either unintentionally or deliberately) in the popular media. Graphical abuses are particularly instructive. Readers should recognize that statistical methods are scientific and with proper education anyone should be able to recognize the good statisticians from the charletons. For now Huff's book is still a good starting place. As a statistician I hate the public image portrayed in the quote above. However, I do sometimes have fun with it myself. As I write this review I am in my office wearing a sweatshirt that reads "When all else fails manipulate the data."

A modern book by a consulting statistician on the same topic is "Common Errors in Statistics and How to Avoid Them" by Phil Good. If you enjoy this book take a look at Good's book also.

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Great intro

By wiredweird HALL OF FAMETOP 1000 REVIEWER on January 12, 2005

Format: Paperback Verified Purchase

-- with no equations. This book really is for every one. In fact, if you're a no-equations reader, this book will be especially helpful.

It shows all the little tricks that advertisers and propagandists, government agencies included, throw at you every day. One, p.85, is an impressive sounding news article about teachers' pay. At first, it looks as if a generous government outlay had doubled or tripled teachers' salaries. Looking closer, however, one sees an odd cluster of unrelated numbers flying in close formation. None of the numbers quoted has any bearing on any other, at least none that the article's reader can discover.

Duff also points out the fallacy of correlation. Oh, it's a useful enough measure, if (!) a number of mathematical requirements are met. It is not causation, however. For example, there is a strong correlation between a school child's height and the child's score on a given spelling test - taller kids do better. The fact is a lot less surprising when you see that first graders tend to be smaller than sixth graders, and tend to know fewer words. Maybe the example sounds silly, but no sillier than lots of the numbers in the news every day.

This is a quick and approachable read, and true even if the examples are now dated. Despite its name, this book really is aimed at honest people, readers who want real understanding of the data thrown at them, and presenters who want their numbers to be understood properly. And best, you don't have to be a mathematician to see what's going on.

//wiredweird

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An Entertaining Primer on the Validity of Statistics

By John Nolley II on January 9, 2004

Format: Paperback

Although "How to Lie with Statistics" is a bit dated (having been written in the 1950's), the principles it puts forth are still valid today--if not moreso than ever--and the material is delivered in clear, concise, and even entertaining anecdotes and illustrations.
How often do you hear statistics bandied about in the media or used to try to prove some special-interest point? "Of course" the people quoting the figures must be right with numbers on their sides... until you look at just how those numbers were arrived at.
This book isn't truly a guide on how to lie with statistics, but it is an excellent text that informs the reader both how others will lie to them using statistics and on how to interpret the validity of purported statistical data.

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Most Recent Customer Reviews

A Classic

Using lots of examples to show how statistics are misused (often intentionally), this entertaining read puts you in the critical frame of mind that you should always use analyze a... Read more

Published 5 days ago by P. Martin

Get this!

A must read book for all people from every walk of life.

Published 10 days ago by Nate Boscaljon

Boring

Boring. I didn't (could not) read it all. Sounds like a time waster.
The cover has ALL you need... People can LIE with Statistics. Period.

Published 14 days ago by Amazon Customer

I enjoyed the writing and I think it will be a ...

As someone who studied stats in school, there wasn't a lot in the book that I wasn't already familiar with. Read more

Published 27 days ago by William Higgins

Dated!

Very dated book with references that are difficult to relate to.

Published 27 days ago by S Kett

Five Stars

Excellent

Published 1 month ago by Richard

Classic Handbook on the Abuses of Statistics

This classic text is perfect for a quick understanding or a review of how statistics are abused. The antiquated examples reinforce that some things never really change. Read more

Published 2 months ago by A Cook

Required Reading

World's Slimmest Bible. This should be required reading for statisticians, for "analysts", for news-graphic creators, and for... Read more

Published 2 months ago by W. H. Bent Jr.

Reveals a lot of ways to spot flawed information from data.

Published 2 months ago by Skyline

how great to find out how it's done

In the craze of today's presidential election, when polls, samples, interviews with a group of 5 voters (who apparently represent the 300 million rest of us), how great to find out... Read more

Published 2 months ago by Beryl the Bookworm

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