- ISBN13: 9780393310726
- Condition: NEW
- Notes: Groundbreaking New from Publisher. No Remainder Mark.
Product Description
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 fool rather than inform.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
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It discussed statistics, I guess, but it didn’t discuss anything that would be taught in a college statistics course.
I was hoping to be provided with material on how to calculate and come up with something statistically. It only talked about people misusing numbers.
I reckon that most high-school students are likely to already have most of the information provided in the book. I am 35 and was mostly disappointed.
Rating: 1 / 5
It’s a cute book, although utterly misleading. The Atlantic wrote: “A pleasantly subversive small book, guaranteed to undermine your faith in the almighty statistic.”
The fact of the matter is that when proper, statistically sound data gathering and analysis methods are employed, the statistics not only do not lie, but they also reveal the nature and extent of the errors inherent in the results.
I know – among other things, I’m a professsional statistician.
In fact, it was my profession in statistics that steered me into network analysis, which is a statistician’s dream world. Large corporations must figure out where the bottlenecks reside, and how to combat them in the most cost-effective, time-valued, long-term manner.
To do this properly, it takes an individual who knows Finance, Statistics, and Networks.
Bottom lie: Statistics themselves don’t lie. But, the improper use of statistics can lead to erroneous conclusions.
Rating: 1 / 5
The information was presented in simple language for the non-statistician. It was helpful to consider how statistics are presented and how they can be interpreted. The examples were outdated.
Rating: 2 / 5
It’s been a month now and I still haven’t received this book. Links to contact the seller weren’t working a week ago so that’s a small odd, but I’m guessing my order didn’t get processed for some reason.
Rating: 1 / 5
When How to Lie — was first published in 1954, when a $10,000 salary was considered munificent, a Yale graduate at $23,000 would have been considered outstanding. And a CEO at $48,000 grossly overpaid. For those who can still reckon in 1954 terms, relating to the number examples in this book is possible. For all others, when the book was re-copyrighted in 1993, the number examples should have been made current.
Rating: 4 / 5