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Subject Area(s): Statistics, Health Care, Marketing
Biography:
A Honolulu native, Bruce Cooil worked as a biostatistician at the Institute of Health Research in San Francisco before pursuing his doctoral studies at the Wharton School. At Wharton, he was awarded the Dean's Fellowship in Statistics and the Bursk Prize. After earning his Ph.D., Professor Cooil joined Owen's faculty in 1982. At Owen, he has received the Dean's Award for Research Productivity (2004) and Research Excellence (2003), and several teaching awards, including election as "Outstanding Professor" by the executive MBA class of 2004, and the Dean's Award for Teaching Excellence. Overall, his publications have received over 1400 citations and have appeared in business, statistics and medical journals, including the Journal of Marketing Research, the Journal of Marketing, Marketing Science, Psychometrika, the Journal of the American Statistical Association, the Annals of Probability, Circulation, and the New England Journal of Medicine.
Cooil has developed reliability estimators for qualitative data that are used widely in business and management, communication, applied psychology, psychometrics, health care and in the natural sciences. For his collaborative work in marketing, he has also received several awards, including the Lehmann Award (2001) and the H. Paul Root Award (2007). In medicine, he and his collaborators have developed a significantly more accurate 'volumetric' measure of coronary calcification by electron beam tomography which can be used to follow the progression of atherosclerosis, and to monitor the effects of treatment in individual patients. This approach has been shown to significantly reduce mortality and morbidity rates of coronary heart disease while providing substantial cost savings. He is also a co-author of the textbook: Statistics for Applied Problem Solving and Decision Making, with R.J. Larsen and M.L. Marx, Belmont, CA: Duxbury, 1997. Cooil's current research interests include the adaptation of latent class and grade-of-membership models for marketing and medical research, qualitative data reliability, large sample estimation theory and extreme value theory. He has also written and consulted on models for medical malpractice and automobile insurance claims and indemnities. His other research has focused on estimating the probability of rare events, general measures for ordinal association, cross-validation, time-series analysis, and nonparametric prediction rules.
He began his academic career at Stanford University where he earned a Bachelor of Science Degree in Mathematics (with Honors) and a Master's Degree in Statistics. He is a former president of the Stanford Alumni Association of Tennessee, and has served as Council Representative for the American Statistical Association's Section on Statistics in Marketing, and on the American Statistical Association's Council of Sections Fiscal Oversight Committee (Curriculum Vitae).
Education
B.S., Mathematics, Stanford University, 1975 M.S., Statistics, Stanford University, 1976 Ph.D., Statistics, University of Pennsylvania, 1982
Education: B.S., Mathematics, Stanford University, 1975M.S., Statistics, Stanford University, 1976Ph.D., Statistics, University of Pennsylvania, 1982
Course(s) Taught: - EMGT 782: Statistics for Management Decisions - MGT 480: Business Forecasting
Other Course(s): Mathematical Statistics, Bayesian Decision Analysis,Exploratory Data Analysis & Modeling,Lifetime Distributions & Survival Analysis,Data MiningAdvanced Forecasting Models
Research Interest(s): Statistical inference, probability, and applications in business. Specific interests in latent class models for marketing and medical research, qualitative data reliability, large sample estimation theory and extreme value theory.
Podcast(s) & Video:
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