Product Description

This book introduces the reader to the niceties of samples (random or stratified random), averages (mean, median or modal), errors (probable, standard or unintentional), graphs, indexes and other tools of democratic persuasion.

Product Details

• Amazon Sales Rank: #23066 in Books
• Published on: 1991-12-12
• Original language: English
• Binding: Paperback
• 128 pages

About the Author
Darrell Huff (1913-2001) was a professional writer. He lived in Carmel, California.

Customer Reviews

Easy to read, but detailed and enlightening.
I first read this book when I was about 12, and re-read it now that I'm in my 20s, and am amazed by how good it is. It's got the complexity of a textbook, but the writer has no pretensions and has managed to get the information across in a way so simple a child can easily read the book and understand some of his lessons and examples.

There are plenty of lessons about how we should interpret the numbers we come across every day in adverts and (potentialy biased) news reports and there is nobody living in the developed world who can't benefit from the enlightenment that this brings.

The only disappointing aspect of this book is that it's so short, an accomplished reader with some knowledge of statistics could get through the book in a single (if lengthy) sitting.

Invaluable basic primer on how not to use numbers
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.

A primer for critical thinking
While anyone who has dealt with statistics in a professional capacity is probably familiar with the contents already, it is still a handy little reference. And for anyone in an introductory course of study or who is simply concerned enough to wonder about the truth of what they read, this is absolutely invaluable.

It is not a long book, and some of the examples are dated (physicians recommending brands of tobacco, for instance), but the meat of the book is both accurate and extremely readable. It covers the ways that statistics can be made to show pretty much anything, both through deliberate manipulation and through simple sloppiness. The main chapters cover issues such as inadequate and biased samples, how to provide subtly and not-so-subtly misleading (though technically accurate) visual charts and representations, how to manipulate perception by eliminating inconvenient precision and adding spurious precision, how to manipulate perception by supplying numbers without context or by simply leaving inconvenient facts out, and how to confuse people thoroughly about correlation vs. cause-and-effect. The final chapter provides a nice summary: the questions you absolutely must ask about any figure you are presented with, in order to judge its worth.

As the author himself says, it may read something like a graduate text on dishonesty, but one can assume that people who deliberately wish to mislead have figured out how already; this is to educate the honest person who wishes to be alert. It is frequently used as a text in undergraduate statistics courses, for good reason.