If you’re a practicing scientist, you probably use statistics to analyze your data. From basic t tests and standard error calculations to Cox proportional hazards models and geospatial kriging systems, we rely on statistics to give answers to scientific problems.
This is unfortunate, because most of us don’t know how to do statistics.
Statistics Done Wrong is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. Many of the errors are prevalent in vast swathes of the published literature, casting doubt on the findings of thousands of papers. Statistics Done Wrong assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.
Dive in: the whole guide is available online!
New! The Second Edition of Statistics Done Wrong includes many changes, including new examples and more misconceptions. If you find any errors or typos, or want to suggest other popular misconceptions, contact me.
In my quest to build the most comprehensive collection of statistical error available, I’m revising Statistics Done Wrong further, into a complete book with new sections on statistical modeling, additional mathematical explanations, and more detail. Use the box at the right to sign up to receive updates by email.