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2011 Hoppe Research Professor Award-- Dr. Andrew Neath

The Hoppe Research Professor Awards are made to SIUE faculty members in order to recognize and support individual programs of research or creative activities. These awards recognize faculty members whose research or creative activities have the promise of making significant contributions to their fields of study. The 2011 (FY2012-13) Hoppe Research Professor Award has been awarded to:

Dr. Andrew Neath, Professor, Department of Mathematics and Statistics
"Statistical Model Selection and Decision Making in the Presence of Uncertainty."

Dr. Neath has been at SIUE since 1994. He received the Hoppe award for his research project titled "Statistical Model Selection and Decision Making in the Presence of Uncertainty". In statistical decision problems, one must determine how best to use available data in deciding which of several options to pursue. The applications to this work are numerous. For example, a health professional may need to decide on the course of treatment for a patient, a quality engineer may need to decide if a production is operating correctly, or a scientist may need to decide which of several competing theories provides a proper explanation for the phenomenon under investigation. The traditional approach to statistical decision making is hypothesis testing. The shortcomings of traditional hypothesis testing are now being noticed. For example, the phrase "statistical significance", although commonly used in the scientific literature, is quite misleading in that traditional hypothesis testing can not be used to provide strong evidence of a correct decision. A consequence of the reliance on traditional hypothesis testing is an abundance of results which are established as "statistically significant", but fail to be validated when replication is attempted. Dr. Neath plans on pursuing a Bayesian solution to the problem of statistical decision making. A major advantage of a Bayesian approach to statistical decision making is the ability to assess a level of belief in the ultimate decision. Dr. Neath is receiving funding from the STEP program and the Baich award to study the role of social choice theory in statistical model selection. Funding from the Hoppe award will allow Dr. Neath to expand the scope of his study. Decision making on the basis of observed data is at the forefront of science. It is vital for statisticians to continually assess the procedures put forth to the scientific community at large. The ultimate goal of Dr. Neath's research program is provide a more coherent approach for practitioners to use in solving statistical decision problems.

Dr. Neath is a Professor of Mathematics and Statistics in the SIUE College of Arts and Sciences. He received his Ph.D. in 1994 from the University of California Davis. His current research interest is the utilization of Bayesian methodology in statistical model selection problems. He is the author of 36 research papers, and has supervised 28 Masters' thesis papers.

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