Thursday, December 6, 2018
12:00 noon – 1:00 p.m.
Building 9, hall 1, room 2322
A lecture by Jim Berger, arts and sciences professor of statistic, Duke University.
Abstract:
Professor Berger will discuss three of the statistical causes for the lack of reproducibility of science, along with a suggested cure. The first cause is the common misinterpretation of p-values; the second is the frequent lack of sufficient adjustment for multiple testing; the third is the common ignoring of optional stopping when testing. The suggested cure for all three is to use odds of hypotheses as the basic inference tool. Surprisingly, this can be done in a way that simultaneously accommodates both frequentist and Bayesian reasoning.
Biography:
Jim Berger is an arts and sciences professor of statistics at Duke University. His current research interests include Bayesian model uncertainty and uncertainty quantification for complex computer models. Berger was president of the Institute of Mathematical Statistics from 1995-1996 and of the International Society for Bayesian Analysis in 2004. He was the founding director of the Statistical and Applied Mathematical Sciences Institute, serving from 2002-2010. He was co-editor of the Annals of Statistics from 1998-2000 and was a founding editor of the Journal on Uncertainty Quantification from 2012-2015. Berger is a fellow of the ASA and the IMS and has received Guggenheim and Sloan Fellowships. He received the Committee of Presidents of Statistical Societies “President’s Award” in 1985 and was the COPSS Fisher lecturer in 2001 and the Wald lecturer of the IMS in 2007. He was elected as a foreign member of the Spanish Real Academia de Ciencias in 2002 and was elected to the US National Academy of Sciences in 2003. He was awarded an honorary Doctor of Science degree from Purdue University in 2004 and became an honorary professor at East China Normal University in 2011.
For more information, please contact Prof. Håvard Rue at haavard.rue@kaust.edu.sa.
A light lunch will be served at 11:45 a.m.
