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

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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.

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Bayesian Networks for the Uninitiated, with David Barton

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Bayes’ Theorem. Credit: Daniel Hjort, CC BY-NC-ND 2.0.

Baffled by Bayesian statistics? You’re not alone.

Join us as we speak with Dr. David Barton, Guest Editor of the special series “Bayesian Networks in Environmental and Resource Management,” to discuss the basics of Bayesian approaches in environmental management. The series is composed of seven case study articles, each of which applies the Bayesian network approach to environmental and resource management problems around the world. Access the series in the July 2012 issue of IEAM.

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Well Past Time to Stop Using NOELs and LOELs, with Wayne Landis and Peter Chapman

Drs. Landis and Chapman are authors of an editorial in the October 2011 issue of IEAM entitled, “Well Past Time to Stop Using NOELs and LOELs.” The editorial was essentially a call to end the use of these two measures in favor of more statistically robust approaches. Join us as we hear more from Wayne and Peter on their call to move away from relying solely on hypothesis testing.

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