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 swaths of the published literature casting doubt on the findings of thousands of papers. The first half of statistics done wrong are plain english essays on various problems encountered in modern science related to statistics problems which crop up again and again such as the multiple comparison problem over reliance on p values etc similar to motulsky reinhart prefers 95 confidence intervals. Statistics done wrong the woefully complete guide. Maybe the limitation in the exercise is that statistics appears so much fraught with dangers of over interpretation and false positives and that everyone except physicists is bound to make such invalidated leaps in conclusion willingly or not that it sounds like the statistical side of godels impossibility theorem. Statistics done wrong the woefully complete guide by alex reinhart a graduate student in statistics at carnegie mellon university is a guide to many common errors in statistical analyses in scientific research papers with many examples drawn mostly from the biology and medical research literature
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