Statistics is hard, often counterintuitive, and burdened with esoteric mathematical equations. Statistics classes can be boring and demanding; students might be tempted to call it “Sadistics.” Good statistics are essential to good research; unfortunately many scientists and even some statisticians are doing statistics wrong. Statistician Alex Reinhart has written a helpful book, Statistics Done Wrong: The Woefully Complete Guide, that every researcher and everyone who reads research would benefit from reading. The book contains a few graphs but is blissfully equation-free. It doesn’t teach how to calculate anything; it explains blunders in recent research and how to avoid them.
Inadequate education and self-deception
Most of us have little or no formal education in statistics and have picked up some knowledge in a haphazard fashion as we went along. Reinhart offers some discouraging facts. He says a doctor who takes one introductory statistics course would only be able to understand about a fifth of the articles in The New England Journal of Medicine. On a test of statistical methods commonly used in medicine, medical residents averaged less than 50% correct, medical school faculty averaged less than 75% correct, and even the experts who designed the study goofed: one question offered only a choice of four incorrect definitions.
There are plenty of examples of people deliberately lying with statistics, but that’s not what this book is about. It is about researchers who have fooled themselves by making errors they didn’t realize they were making. He cites Hanlon’s razor: “never attribute to malice that which is adequately explained by incompetence.” He says even conclusions based on properly done statistics can’t always be trusted, because it is trivially easy to “torture the data until it confesses.” (more…)