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Spotting and Avoiding Them


Medical researcher John P. A.  Ioannidis has asserted, "It can be proven that most claimed research findings are false."[1]. There are some criticisms of his "proof"[2], but even most of his critics agree that there is a high incidence of false conclusions in  research papers. Indeed, we frequently hear in the news results of a research study that appears to contradict the results of a study published just a few years ago. Although there is occasional deliberate falsification, most of the problem comes from lack of understanding of statistical techniques, their proper use, and their limitations.

The intent of this website is to discuss some of the common mistakes made in using statistics, and  offer suggestions on how to avoid making them.

Types of mistakes

Many mistakes in using statistics fall into one of the following categories:

Suggestions for reducing the incidence of mistakes in using statistics



Table of Contents


1. Ioannidis JPA (2005) Why Most Published Research Findings Are False. PLoS Med 2(8): e124. doi:10.1371/journal.pmed.0020124, available at
See also the following popular press articles:
and the semipopular article by Andrew Gelman and David Weakliem, Of Beauty, Sex, and Power, The American Scientist, 97(4), July-August 2009,

2.  e.g., Steven Goodman and Sander Greenland. "Why Most Published Research Findings Are False: Problems in the Analysis". PLoS Medicine 4 (4): e168. doi:10.1371/journal.pmed.0040168; Pauker SG (2005) The Clinical Interpretation of Research. PLoS Med 2(11): e395. doi:10.1371/journal.pmed.0020395; Wren JD (2005) Truth, Probability, and Frameworks. PLoS Med 2(11): e361. doi:10.1371/journal.pmed.0020361; The PLoS Medicine Editors (2005) Minimizing Mistakes and Embracing Uncertainty. PLoS Med 2(8): e272. doi:10.1371/journal.pmed.0020272

Last updated April 10, 2012.