Scientific progress depends on good research, and good research needs good statistics. However, statistical analysis can be tricky to get right, even for the best and brightest. 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 help you keep your research blunder-free. 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 approach statistics. You'll find advice on asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan. Additionally, you'll learn how to think about p-values, significance, insignificance, confidence intervals, and regression, as well as how to choose the right sample size.