Exercises and Solutions in Biostatistical Theory: 1st Edition (e-Book) book cover

Exercises and Solutions in Biostatistical Theory

1st Edition

By Lawrence Kupper, Brian Neelon, Sean M. O'Brien

Chapman and Hall/CRC

420 pages

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Description

Drawn from nearly four decades of Lawrence L. Kupper's teaching experiences as a distinguished professor in the Department of Biostatistics at the University of North Carolina, Exercises and Solutions in Biostatistical Theory presents theoretical statistical concepts, numerous exercises, and detailed solutions that span topics from basic probabilit

Table of Contents

Basic Probability Theory. Univariate Distribution Theory. Multivariate Distribution Theory. Estimation Theory. Hypothesis Testing Theory. Appendix. References. Index.

About the Authors

Lawrence L. Kupper, Ph.D., is an emeritus alumni distinguished professor of biostatistics at the University of North Carolina at Chapel Hill. Dr. Kupper has received several teaching and research awards during his career and has been involved with many research areas in the health sciences, including epidemiology, environmental and occupational health, maternal and child health, and medicine. His research interests concern the development of innovative biostatistical methods for the design and analysis of public health research studies.

Brian H. Neelon, Ph.D., is a research statistician with the Children's Environmental Health Initiative (CEHI) in the Nicholas School of the Environment at Duke University. Before working at Duke University, Dr. Neelon was a Postdoctoral Research Fellow in the Department of Health Care Policy at Harvard University. He earned his Ph.D. from the University of North Carolina. His research interests include Bayesian methods, longitudinal data analysis, finite mixture models, and health policy statistics.

Sean M. O'Brien, Ph.D., is an assistant professor of biostatistics and bioinformatics at the Duke University School of Medicine. Dr. O'Brien earned his Ph.D. from the University of North Carolina. His research interests include statistical methods for healthcare provider profiling, observational studies, and Bayesian data analysis.

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General