How to Lie With Statistics
By: Darrell Huff
How to Lie with Statistics is a book written by Darrell Huff in 1954 presenting an introduction to statistics for the general reader. Huff was a journalist who wrote many "how to" articles as a freelancer, but was not a statistician. Although this book is 50 years old this year, its wisdom is needed now more than ever, as increasing computer power and our headline-obsessed media look set to drown us all in a sea of "statisticulation". This is the word coined by Darrell Huff to describe misinformation by the use of statistical material. Biased samples, dubious graphs, semi-attached figures: he describes all the usual suspects clearly and simply, rounding off with the most useful topic of all: How to Talk Back to a Statistic
The book is a brief, breezy, illustrated volume outlining common errors, intentional and unintentional, associated with the interpretation of statistics, and how these errors can lead to inaccurate conclusions. In the 1960s and '70s it became a standard textbook introduction to the subject of statistics for many college students. It has become one of the best-selling statistics books in history, with over one and a half million copies sold, even though the monetary examples have become dated because of inflation. Here Huff explains "how to look a phony statistic in the eye and face it down; and no less important, how to recognize sound and usable data in the wilderness of fraud". Look for bias, he advises, conscious and unconscious; find out "who-says-so" (if an "O.K. name" is cited, make sure it stands behind the information, not merely beside it); ask how the authority knows; try to find out what's missing; check whether the raw figure justifies the conclusion drawn and, most straightforwardly of all, ask yourself if the statistic makes sense.
Themes of the book include "Correlation does not imply causation" and "Using random sampling". It also shows how statistical graphs can be used to distort reality, for example by truncating the bottom of a line or bar chart, so that differences seem larger than they are, or by representing one-dimensional quantities on a pictogram by two- or three-dimensional objects to compare their sizes, so that the reader forgets that the images do