Get Real! Stuart Hurlbert on Pseudoreplication and Other Sins of Statistical Analysis

Experimental zebrafish (Danio rerio). Credit: Novartis AG, CC BY-NC-ND 2.0.

Think you know stats? Stuart Hurlbert first described pseudoreplication—a common but serious statistical error—in 1984. Despite widespread knowledge of the error, pseudoreplication is often misinterpreted, and literature surveys show that the error is on the rise in certain fields. Listen to Hurlbert define pseudoreplication and other related errors, plus hear why we shouldn’t dichotomize results as “significant” and “non-significant,” what’s missing from basics stats courses, and what’s next on his list.

Access the Learned Discourse by Hurlbert and Lombardi in the January 2016 issue of IEAM.

Podcast available on iTunes and YouTube

About the Guest
Hurlbert photoStuart H. Hurlbert is Emeritus Professor of Biology and former Director of the Center for Inland Waters at San Diego State University. His research has been in the areas of salamander migration, pesticide-wildlife relations, effects of fish predation on community structure, ecology of saline lakes, human population politics, and biostatistics. His critiques on the misuse of statistics by scientists have won a number of awards. He is a fellow of the American Association for the Advancement of Science, served as first president of the International Society for Salt Lake Research, and is currently president of Scientists and Environmentalists for Population Stabilization.

Articles Referenced in this Podcast
Stuart H Hurlbert and Celia M Lombardi. Pseudoreplication, one-tailed tests, neofisherianism, multiple comparisons, and pseudofactorialism IEAM 12#1: 196-197.

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