Standard Deviations was the London Times Book of the Week November 2014


Another in the genre that began with the Darrell Huff’s 1954 best-seller, How to Lie with Statistics. If history is any guide, it will likely be ignored by those who do the lying.

In his first book for nonacademic readers, Smith (Economics/Pomona Coll.; Essential Statistics, Regression, and Econometrics, 2011, etc.) delivers an entertaining primer on his specialty, packed with figures, tables, graphs and ludicrous examples from people who know better (academics, scientists) and those who don’t (political candidates, advertisers). “We live in the age of Big Data….Sometimes these omnipresent data and magnificent computers lead to some pretty outlandish discoveries,” writes the author. We hear that children who play competitive sports are confident, so sports must build character. Selection bias makes nonsense of this if only confident children choose to play competitive sports. Enthusiasts tell us how to live to the age of 100, run a profitable business or enjoy a lasting marriage. However, all examine those who have succeeded, ignoring the losers, so survivorship bias renders their advice worthless. Few can resist the fallacious law of averages. If a coin flip turns up 10 heads in a row, the 11th flip is not more likely to be tails. If you fly regularly, the odds that your plane will crash do not increase. Good and bad luck do not even out. Chance is just chance. The Texas sharpshooter peppers the side of a barn and then draws a bull’s eye around the densest clump of holes. In other words, even honest observers find patterns in random data and can’t resist explaining them. We believe these stories if they seem reasonable and love them if they’re provocative—see Freakonomics, whose authors have admitted some mistakes.

“We are too easily seduced by explanations for the inexplicable,” writes the author in this amusing, informative account of how many arguments are backed by meaningless statistics.

A very entertaining book about a very serious problem. We deceive ourselves all the time with statistics, and it is time we wised up. Robert J. Shiller, winner of the Nobel Prize in Economics and author of Irrational Exuberance

The challenge of sorting through conflicting advice about health, finance, business, education and parenting and other critical issues is one of the great problems of modern times, thanks to a vast, intense bombardment via the media of authoritative, sciencey-sounding claims that appear to give us the unvarnished, data-backed truth. Not so fast, says Gary Smith--most of the stuff we're fed is polluted with any of a long list of distortions, biases, and plain old errors. Smith sets the record straight, via hugely engaging case studies and anecdotes. It's the most fun you can have while learning how to avoid being led astray by the hordes of sloppy, self-serving—if often well-meaning—data-mongers in academia and the media.David H. Freedman, Atlantic contributor, author of Wrong: Why Experts Keep Failing Us—And How to Know When Not to Trust Them

 Gary Smith is brilliant when it comes to writing lively and understandable statistical analysis, and Standard Deviations is his best work to date. It joins Darrell Huff's How to Lie With Statistics as a 'must read' classic in the field.Woody Studenmund, Laurence de Rycke Professor of Economics, Occidental College

It's entertaining; it's gossipy; it's insightful; it's destined to be a classic. Based on a lifetime of experience unravelling the methodical blunders that remain all too frequent, this book communicates Gary Smith’s wisdom about how not to do a data analysis. Smith’s engaging rendering of countless painful mistakes will help readers avoid the pitfalls far better than merely mastering theorems. Edward E. Leamer, Chauncey J. Medberry Professor, UCLA

Standard Deviations shows in compelling fashion why humans are so susceptible to the misuse of statistical evidence and why this matters. I know of no other book that explains important concepts such as selection bias in such an entertaining and memorable manner.Richard J. Murnane, Thompson Professor of Education and Society, Harvard Graduate School of Education.

Gary Smith's Standard Deviations is both a statement of principles for doing statistical inference correctly and a practical guide for interpreting the (supposedly) data-based inferences other people have drawn.  The book is cleverly written and engaging to read, full of concrete examples that make clear not just what Smith is saying but why it matters.  Readers will discover that lots of what they thought they'd learned is wrong, and they'll understand why. Benjamin M. Friedman, William Joseph Maier Professor of Political Economy, Harvard University

Standard Deviations will teach you how not to be deceived by lies masquerading as statistics. Written in an entertaining style with contemporary examples, this book should appeal to everyone, whether interested in marriages or mortgages, the wealth of your family, or the health of the economy. This should be required reading for everyone living in this age of (too much?) information. Arthur Benjamin, Professor of Mathematics, Harvey Mudd College and author of Secrets of Mental Math 

Statistical reasoning is the most used and abused form of rhetoric in the field of finance. Standard Deviations is an approachable and effective means to arm oneself against the onslaught statistical hyperbole in our modern age. Professor Smith has done us all a tremendous service. Bryan White, Managing Director, BlackRock, Inc.

Humans are pattern-finding primates, but which patters are real and which are illusory? Science is the best tool we have for answering the question, but as Gary Smith reveals in this deeply insightful skeptical analysis of the use and abuse of statistics, the numbers never just speak for themselves. They are filtered through our biased brains, which distort purportedly objective statistics into subjective beliefs we want to be true. His catalogue of mistakes we all make—including and especially scientists—should be memorized by every citizen...and member of Congress. Michael Shermer, publisher of Skeptic magazine, columnist for Scientific American