Statistics Done Wrong: The Woefully Complete Guide

He teaches introductory statistics at Carnegie Mellon.. in physics at the University of Texas, Austin. Alex Reinhart is a statistics Ph.D student at Carnegie Mellon University who received his B.S

But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong.Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. Statisticians: Give this book to everyone you know.The first step toward statistics done right is Statistics Done Wrong.. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.You'll find advice on:Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the planHow to think about p values, significance, insignificance, confidence intervals, and regressionChoosing the right sample size and avoiding false positivesReporting your analysis and publishing your data and source codeProcedures to follow, precautions to take, and analytical software that can helpScientists: Read this concise, powerful guide to help you produce statistically sound research. Scientific progress depends on good research, and good research needs good statistics

Dimitri Shvorob said Appealing. Let me front-load the criticism. I wish an experienced statistics instructor had reviewed the manuscript. The book does better in its second half, where it discusses what I would call problems with empirical-research culture, than in its first half, which has more textbook statistics. The author neglects to explain the basics - things like "sample", "statistic", "sampling distribution", "conditional probability" - and often confuses matters by bringing in issue Y when. Essential Reading for Anyone Who's Serious About Research I ADORE THIS BOOK and plan on sharing it with many of my students. Why? We want our research to be rigorous, but many of us rely on hazy knowledge gained from basic courses on introductory statistics many years ago. It can also be difficult to grasp the subtle details of when and how our techniques will be appropriate as we pursue statistically sound research.Reinhart's book helps fill that conceptual gap, and it does it extremely well with a fresh and inviting writin. "If you worship science, you best read this book." according to Robert A. Avila. A fantastically interesting book. Anyone who loves numbers, and loves science will appreciate the compiled research and examples Alex Reinhart published here. Many times, reading the stories and statistical studies, I thought back to my Ivy League university experience. Often times, a professor quoted some study based on a particular topic, described the nature of the study, and then presented the conclusion. Too many times, the conclusion struck me as nonsensical or

"If you analyze data with any regularity but aren't sure if you're doing it correctly, get this book." -- Nathan Yau, FlowingData"Of all the books that tackle these issues, Reinhart's is the most succinct, accessible and accurate." -- Tom Siegfried, Science News"A spotter's guide to arrant nonsense cloaked in mathematical respectability." -- Gord Doctorow, BoingBoing