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Irving Geis

Darrell Huff

How to Lie with Statistics Reissue Edition

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

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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-10

0393310728
ISBN-13

978-0393310726
Edition

Reissue
Publisher

W. W. Norton & Company
Publication date

October 17, 1993
Language

English
Dimensions

5.5 x 0.4 x 8.3 inches
Print length

144 pages
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Editorial Reviews

Amazon.com Review

"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!"
― New York Times

"A pleasantly subversive little book guaranteed to undermine your faith in the almighty statistic."
― Atlantic

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 ‏ : ‎ 3.84 ounces
Dimensions ‏ : ‎ 5.5 x 0.4 x 8.3 inches

Best Sellers Rank: #16,740 in Books (See Top 100 in Books)
- #4 in Business Statistics
- #6 in Statistics (Books)
- #11 in Probability & Statistics (Books)

Customer Reviews:
4.5 4,036 ratings

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Irving Geis
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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.
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Darrell Huff
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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.
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Jhan Kevin Gil Marin

Awesome book

Reviewed in the United States on October 7, 2023

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It's easy to read. Present the math in a simple way and explains how the statistics can be used to tell totally different stories from the same data.

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CDianne

Classic Book on the title!

Reviewed in the United States on August 8, 2023

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I am a scientist and I use this book to help people and students understand how we can be dupped with numbers. The book is straightforward, easy to understand and has absolutely CORRECT information. You do not have to be a scientist to use this book. Anyone who does presentations with numbers in it needs to be sure to understand the straightforward information so they can be protected against being tricked and ready for questions about how they have prepared their own charts!
Great info! This is a classic book!

2 people found this helpful

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Charming if a bit dated and oversimplified

Reviewed in the United States on July 27, 2019

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In 2016, all the best money was on Hillary Clinton to defeat Donald Trump in the U.S. Presidential election. Massive polls analyzed by highly-credentialed experts said so. The election went the other way. How could the analysts have gotten it so wrong? A potential answer is found in the pages of this short book written more than sixty years earlier by Darrell Huff and charmingly (if whimsically) illustrated by Irving Geis.

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.

127 people found this helpful

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S

Should be Mandatory Read for All High Schoolers

Reviewed in the United States on March 26, 2023

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Don't know why the educational system doesn't include books like this as a mandatory read for all students.

One person found this helpful

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Isa

Love this

Reviewed in the United States on May 23, 2023

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Using data to influence other is such a good way if you are beginner of the career, nobody will ever believe what you say so might as well use the data to gain credibility.

2 people found this helpful

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GBHmagic

great book

Reviewed in the United States on May 24, 2023

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Not long but full of information everyone shoukd read at least once. The book shows you how statistics can be used to manipulate data into just about anything.

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Brit

Influential book to me.

Reviewed in the United States on February 25, 2016

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I'm a college student who had to buy this book for a math class. We had a list of books to choose from and I chose this because it seemed to be one of those interesting debunking type writing pieces that give an alternate perspective on something so commonly followed.
With statistics, we see them everywhere and spewing from people's mouths constantly. But where do they come from and why are they unreliable and in what cases are they unreliable?
Darrell Huff kind of hits all aspects of statistics, and is sure that he hasn't crossed his own lines of creating bias; throughout the book he addresses each side the story. What sides am I referring to? The statistician's point of view, whoever's hands it was transferred to thereafter, the media that project this news to viewers, and the viewers point of view. He does this all with such a sense of reliability, because he never fails to leave out an aspect that would undermine his conclusions.
I found a lot of great information in this book, some that has reinforced my beliefs about statistics and others that have provided me with new views on information. With increasing amounts of information available, and that instant communication that allows us to share information faster, we need people to be reading more books like this so they avoid learning a bunch of value-less information from people who haven't "done their homework."
Sometimes statistical deceit is unintentional, while other times it's deliberate. Huff examines each cases, and attempts to provide understanding to all of his readers as to how we can avoid this and the 5 questions we can ask ourselves when we approach information.

If you've either:
- Wondered about news information and how it's history has influenced citizens (and how it really still applies)
- Needed refreshers on the importance of statistics as well as how to approach them
- Struggled with reading statistics or producing statistics
- Enjoyed being offered alternate perspectives on widely accepted practices like presenting information through statistics
- Curious about where people get their information, and why they're quick to spew statistics like it's true knowledge
THEN READ THIS BOOK! :)

101 people found this helpful

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Sphex

I have often seen those damned little dots before, but I never knew until now what they meant

Reviewed in the United Kingdom on December 18, 2008

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There is still much to lament in our ruling classes, but thank goodness we are no longer led by the likes of Lord Randolph, whose epiphany with regard to the decimal point is quoted above. However low your opinion of contemporary politicians, Gordon Brown is unlikely to mistake ".34 per cent" for "34 per cent" (although our financial ruling class would probably reward themselves handsomely for being out by only a factor of a hundred). Before we congratulate ourselves too readily for our mathematical sophistication, we should reflect upon the salutary fact that Darrell Huff's classic text is as necessary today as it was when it was first published over half a century ago. It is remarkable that, despite certain figures showing their age (we might be heading back to an average wage of £1,400 but we're not quite there yet), there is nothing dated about his style. A maths book on statistics from the fifties? If this seems as appetizing as a cold spam butty during a power cut, you're in for a surprise. That decade was not entirely in black and white.

If you spotted the fast one I pulled in the first paragraph, you're either one of "the crooks" who already know these tricks or else are an honest soul who has learned them "in self-defence". Hence the title of this fantastic little book: knowing how a burglar thinks helps secure your house. Most of the time, I would pass over the phrase "average wage" without a second glance. We all know what an average is, don't we? Distant maths lessons are just that for most of us, and even if I'd dredged up the question - what kind of average? - would I have been bothered to ask it? Complacency translates into vulnerability.

"When you are told that something is an average you still don't know very much about it unless you can find out which of the common kinds of average it is - mean, median, or mode." Without a clear understanding of these different kinds of average, you have to hope it doesn't really matter which one is being used, but this is only the case "when you deal with data... that have the grace to fall close to what is called the normal distribution." Otherwise, it makes a big difference, so much so that, "as usually is true with income figures, an unqualified 'average' is virtually meaningless."

Advertisers, of course, are among the most culpable and capable when it comes to lying with statistics (although at least their motives are plain). It is typical of Huff's sense of mischief that, alongside the calculations, he presents us with an ethical dilemma of enormous proportions: should we feel sorry for advertisers who are themselves victims of statistical skulduggery? For example, a magazine publisher is happy to state the median age of its readership, while leaving the kind of average for incomes "carefully unspecified". "Could it be that the mean was used instead because it is bigger, thus seeming to dangle a richer readership before advertisers?"

This is a short book, made even shorter by pictures of cows and charts that take up half a page. (How the innocent-looking graph can be manipulated by adding "schmaltz" is another example of Huff's style: a simple unpicking of the familiar to demonstrate an important point.) It is also unreasonably funny in parts. I don't recall maths, let alone statistics, ever being this entertaining at school. And yet the intellectual content is not compromised. Huff's message is a serious one and perhaps more important now, since our propensity for attaching numbers to almost anything shows no sign of diminishing. It ought to be common knowledge that samples can be "biased by the method of selection", that "well-biased samples can be employed to produce almost any result anyone may wish", that it can be difficult to obtain "a representative sample... one from which every source of bias has been removed", that people who answer survey questions have "a desire to give a pleasing answer", that strange results "crop up when figures are based on what people say".

Most of us can understand these ideas when they are explained by someone like Huff (although it might help not to be an aristocrat). If we're honest, out in the wild without a guide, we're not so sure. Have you ever been scared by "accident statistics"? Would the fact that more people "were killed by aeroplanes last year than in 1910" give you pause for thought? Are modern planes really more dangerous? "Nonsense. There are hundreds of times more people flying now, that's all."

"It is sometimes a substantial service simply to point out that a subject in controversy is not as open-and-shut as it has been made to seem." Or, as Goldacre's slogan has it: "I think you'll find it's a bit more complicated than that..." Both belong to that noble tradition of satire with a serious message, and it is a tribute to Huff's writing style that he can end with a quote from Mark Twain that fits perfectly: "There is something fascinating about science. One gets such wholesale returns of conjecture out of such a trifling investment of fact."

12 people found this helpful

Daniel

Interesante

Reviewed in Mexico on August 31, 2023

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Un libro interesante, pero sin mucho orden o seguimiento. Va contando anécdotas sobre cómo la información utiliza erróneamente la estadística y ello lleva a muchos malos entendidos

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Marshall Lord

Invaluable basic primer on how not to use numbers

Reviewed in the United Kingdom on July 27, 2006

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This excellent book is something very unusual.

First, it's about numbers but manages to be both extremely easy to read and very entertaining.

Secondly, although it is so accessible that a ten-year old of average intelligence should be able to understand everything in this book, the points it makes are so universal in application that even someone with much greater mathematical knowledge - and I write this as a graduate with two degrees in a discipline which requires statistical understanding - can find it full of useful reminders and even the odd valuable idea you might not have thought of or heard of.

The book is about how numbers can be manipulated, by accident or design, to trick people into making false conclusions, and how to spot when you are being fed misleading numbers. In this day and age the ability to spot bad statistics is extremely important to everyone and can literally be a life-saver.

I was very surprised indeed to see that a previous reviewer had described this book as "not for everyone." I could not disagree more strongly.

If every voter read this book, fewer bad politicians would be elected on the basis of dishonest campaign statistics, if every consumer read it, fewer bad products would be sold on the basis of dishonest advertising statistics, and if every journalist read it there might be less harm done by scare stories based on bad statistics.

Despite the fact that this book was written many years ago, every single word in it is still very relevant today.

However, anyone with a serious interest in the subject who wants an update on some of the more recent examples of how statistics are misused should still start by reading "How to Lie with Statistics" and then follow up with the equally good "Damn Lies and Statistics" by Joel Best, which is more current and nearly as accessible. The two books complement each other very well.

59 people found this helpful

old1

A paradigm shift for many bottom focused companies

Reviewed in the United Kingdom on August 23, 2021

Verified Purchase

Much of the content of this book is not revolutionary but evolutionary, especially if you are an accountancy firm. The major thrust of this book is about agreed accountability, including everyone from the receptionist to the owners and their customers. It covers detailed methods with examples for his own company. It is more evolutionary partly because the basic theory is not new but in the context of an accountancy firm probable revolutionary.

The basic concept is that everyone, including customers, are accountable for their actions and therefore their impact on the success of the company. It highlights an important and fundamental problem associated with bottom-line focussed companies not acknowledging or realizing that not only are customers important to their profit but so are the workforce.

Thiss book addresses this in a well-structured way and is transparent in describing the journey of his company to a point where the profit has increased and staff are engaged with the company as stack holders. An excellent read and well worth giving as a gift, as the methods can be applied to other situation like parenting, relationships to name two.

One person found this helpful

Terry Freedman

Still useful after all these years

Reviewed in the United Kingdom on May 4, 2016

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I first read this book at university, where I was studying statistics as part of my degree. However, it has been in the context of other subjects and, indeed, life in general that this book has proven most useful.

The odd-sounding title is easily explained by the author himself. He says he wrote the book much in the same spirit as a burglar might write an instruction manual on how to break into people’s houses — not so much to make it easier for burglars to do so, but so that home-owners can see where their vulnerabilities lie.

These days, the book seems to be even more relevant. Not only are research findings reported in the papers virtually every day, but in education in particular there are quite a few articles of faith that are based on shaky, and sometimes non-existent, foundations.

With chapters like “The well-chosen average”, “The little figures that are not there” and “The semi-attached figure”, the book makes you look at statistics in a different way.

For example, if you were to read a report that tells us that research has shown that 98% of students derive no benefit whatsoever from using technology, you may have a vague feeling of unease about such a finding. However, having read this book you should be able to re-read the report and spot where the statistical sleight of hand occurred (assuming it did occur, of course).

Then again, there are the endless announcements telling us that eating X wards off cancer, causes cancer, is dangerous for people over 40, is only dangerous if you eat more than one a day etc etc ad nauseous. Again, an insight into how some of the figures cited were derived would be immensely helpful in your decision-making.

Illustrated with cartoons by Mel Calman, this light-hearted and slim volume punches way above its weight. Although it was first published over 60 years ago, in 1954, it is still relevant. It should be on every teacher’s shelf and in every school library.

28 people found this helpful

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