How to Lie with Statistics

This book replaces one that somebody "borrowed" from me at work. I gave it 4 stars only because, being copyrighted in 1954, the examples are very outdated. But it's a great book that should be required reading for anyone who watches the TV news or reads the newspaper.

This is a delightful little book, originally published in 1954, but reprinted in 1993. The information is just as relevant today as it was then - - maybe even more so - - considering the somewhat obvious daily attempts by the media, the government, the academics, and many others to manipulate data to "prove" something that is just not necessarily true or is absolutely untrue (global warming, or evolution, for example). The author approaches his subject matter with a rather light-hearted attitude, which makes the book a joy to read. If the reader is interested in learning how he/she might be being fooled by news reports, technical articles, or surveys, then he/she should read this book. Highly recommended.

This book should be mandatory reading to anyone who reads newspapers. It explains in accessible language some of the tricks used in reporting many kinds of data. The great contribution is not on the techniques per se, but on the basic heuristic of giving a second look to what some things really mean. The book is somewhat old, but it's contents are truly timeless.

All anyone needs to know about statistics is artfully presented in this book. It's main purpose is to help readers decode what others are saying, and how they may be trying to exagerate or distort the facts. AND it is a very fun read -- the historical context is fascinating.

This book has convinced me that basic statistical literacy is vital for 21st century citizenship or we can (and will!) be tricked by intentional and unintentional misuse of statistics. This book provides a GREAT intro to the common ways statistics can be used to mislead-- but it would be great if it were revised to include examples from later than the 1950s!

Written in 1954 but very relevant today. The way statistics are used today confirms that those using stats are confident that those reading them are stupid. This book is easy to read and should be required reading for every high school kid prior to graduation.

I loved this book. Sure the examples are dated, but the message is stupefyingly relevant. It should be required reading for Freshman heading off to University.

The book is selling used for five dollars used. Buy it. You won't have wasted your time.

A pleasant and well illustrated slim book which provides a useful summary of things to watch out for when statistical data is presented. Recommended reading as a gentle introduction to deception with numbers in a variety of sectors

The book was a good primer on looking at statistics from various perspectives and not only from the X & Y axis shared by a chart/graph. This is a book written years ago and hence the examples are out of sync from current world. Also I felt some of the content was fairly basic and most professionals with few years of work experience would be aware of the tricks.
Overall a good read.

Love this little book. I recommend it to anyone starting to study statistics, or to arm themselves as a citizen or a consumer. Fun, easy to read and very important. I first read it as a supplement to my college statistics class over 35 years ago and have read it at least a couple times since. It's timeless.

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. The same old tricks are still used today.

This was purchased as an aid to teaching a citizen journalism class, in particular to discuss how NOT to write stories involving statistics and how to understand when you are being taken on a ride by someone you are interviewing or by recently released studies or government reports. I read it many years ago and was pleased that it was still available for preparation of my course material. It is very helpful.

This book is heavily dated in its examples, but the methodologies it describes are still very applicable today in media and marketing. The title is somewhat of a misnomer as the book is intended to teach how to recognize lies when others use statistics, but there is no reason why the lessons could not be used to do some of your own lying. The text was written by a journalist and is colloquial in nature, making for a quick, entertaining read. Compared to a statistics textbook, it like reading the comics. I highly recommend it for anyone who deals with marketing, the media, or any kind of public affairs. That should cover just about everyone since we are constantly inundated with numbers that never seem quite clear regardless of the source. it is also a great book to help break up the challenges of a statistics course and provide some insight of how all those numbers can be used to teach, inform, or mislead.

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 quantitative argument.

Truly a classic! Clearly explains what statistics can do and what they are intended to show without getting bogged down in the math and mechanics of statistical tests. Although this book was originally published in 1954, the examples and discussion are just as relevant today as they were sixty years ago. Especially recommended for anyone who is taking, or who may need to take, a statistics course.

Darrell Huff's collection of observations is written in 1954, yet it is still lively and useful. We consume every day a lot of facts, figures, we inspect different graphs and tables, but without critical thinking we can easily be deceived. This book provides basic knowledge of how to read and hear figures, numbers, averages and all common tools of statistics. It is easy to understand and comprehend. Even scientists should read this book. When they write about new drugs, about how drugs were tested, when tests are planed, there are often many unnecessary mistakes done. On top of it, Darrell Huff wrote this book funny and popular.

If you do, then you should read this little book. You should also read it if you listen to political speeches. If you're a politician, don't bother, you already know this stuff. Ignore the quaint, outdated data; the underlying theories haven't changed.

The book gives the reader additional perspective on how to view reports - very critical in business especially since the presenter would want you to see what they want to see and not draw attention to other items that may end up sinking their boat.

I was frustrated with the lack of complexity (you don't go past confidence intervals) and silly illustrations instead of images of the news articles, financial statements, and averages he's calculating, but the books message and lesson on sampling bias are priceless and the last chapter sums it up well.

It was a long read for me because his writing voice is old-school (like one of your grandpas smart friends who talks too fast) you might have to adapt to that, but if you want to be brilliant at the basics this book is for you.

After reading this book, people reported being 21.32% sexier in cocktail parties. You may conclude that these fools finally had something interesting to talk about. But further investigations proved that this book increases readers intelligence by 2.15 times which yields to better salaries and by consequence more cocktail parties to attend. Enough rubbish here. I just made up this figures and if you "believed" in any of this nonsense talk don't just buy this book but read it twice.

This book was a quick weekend read. The book was written almost 60 years ago and is still very much applicable. I have read a lot of books on visualization and this was a nice supplement to my tool kit.

Ths book provides valuable insight into how advertising and sensationalist journalism can easily mislead the public without them being aware.

I liked it because in my profession, one has to be careful in reviewing publicized data. I have found that even in scientific journals where it has no place, you can still find many of the examples presented in this book.

In particular, note how one can be easily mislead by extrapolating apparent trends into the future.

This book is a pure pleasure reading for anyone interested in statistics, but wants to have a break from formulas and software! In fact, I would make it a must read for all citizens who are bombarded by over-complicated news about all areas of our life.

I found this book on accident. After reading it I would readily gift it to anyone. Many years after its original publication it still stands up as a straightforward, accessible introduction to some common ways we as consumers are taken advantage of.

Such a classic old book that vividly illustrates the way that statistics are used. Very readable and straight forward and I will give to my kids to read as part of a good general education. They don't write books this way much any more.

Clear explanations of key shortfalls of statistical conclusions which could be misleading. Only thing of this book is the useage of stats in modern day has changed especially in the age of big data. Could be updated.

Do you know the difference between the mean, median, and mode? If yes, chances are this book won't do much for you.

The author addresses how those with an agenda may use any of the "averages" to create a story that fits the narrative they want to tell. Others may rely on very small (or biased) samples to advertise a seemingly large effect that arises just by chance and would go away with a larger (or representative) sample. That is, unfortunately, all the meat there is to this book.

I don't know if I'm just not the target audience for the book. I almost feel bad giving it two stars, as the examples are at times somewhat amusing. However, the book took me only two hours to read, suggesting the "light on content" critique may not be entirely unfair.

As an alternative reading, I would suggest Nate Silver's "The Signal and the Noise: Why So Many Predictions Fail-but Some Don't." Nate Silver's claim to fame is his tremendously successful forecast model for the last two presidential elections. The book deals more with forecasting (and the problems that arise there) than statistics... however, these topics are closely connected and an interest in the latter, I'd imagine, comes with an interest in the former.

Forecasts (maybe even more so than statistics) are something we're exposed to all the time, and we often do not look too closely at how those forecasts came about. Deception there, too, is common: the weather channel, for example, openly admits to exaggerating the chances of rain. Why? If it says there's a 10% chance of rain and it does rain (which, if the model is accurate, happens one every ten times), people will not have planned for it and will be upset that the prediction wasn't "clearer". With 25% chance of rain, people will grab an umbrella and won't have the same bad reaction to unexpected days on which it won't rain. So the interesting twist is that we may be better off with a "wrong" prediction than a right one.