Many issues in the health, medical, and biological sciences are addressed by collecting and exploring relevant data. The development and application of techniques to better understand such data are the fundamental concern of the Group in Biostatistics. The program offers training in the theory of statistics and biostatistics, the computer implementation of analytic methods, and opportunities to use this knowledge in areas of biological/medical research. The curriculum is taught principally by members of the Department of Statistics (College of Letters and Science) and the Division of Biostatistics (School of Public Health) and provides a wide range of ideas and approaches to the analysis of data.
Graduate students in the group have direct access to a variety of specialized computing resources, as well as the services of the campus computing facilities. Research activity of the faculty currently includes biostatistical computing, statistical issues in AIDS research, survival analysis, environmental health, epidemiology, and statistical methods in genetics and computational biology. Projects in research areas provide opportunities for both practical experience and individual research. Cooperation with other departments allows unusually broad and effective training in both theoretical and applied directions.
There is no undergraduate program in Biostatistics.
Biostatistics: MA, MA/PhD, PhD
Faculty and Instructors
+ Indicates this faculty member is the recipient of the Distinguished Teaching Award.
David R. Brillinger, Professor. Risk analysis, statistical methods, data analysis, animal and fish motion trajectories, statistical applications in engineering and science, sports statistics.
Perry De Valpine, Associate Professor. Population ecology, mathematical modeling and statistics.
Sandrine Dudoit, Professor. Genomics, classification, statistical computing, biostatistics, cross-validation, density estimation, genetic mapping, high-throughput sequencing, loss-based estimation, microarray, model selection, multiple hypothesis testing, prediction, RNA-Seq.
Haiyan Huang, Associate Professor. Applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification.
Alan Hubbard, Associate Professor.
Nicholas P. Jewell, Professor. AIDS, statistics, epidemiology, infectious diseases, Ebola Virus Disease, SARS, H1N1 influenza, adverse cardiovascular effects of pharmaceuticals, counting civilian casualties during conflicts.
Michael J. Klass, Professor. Statistics, mathematics, probability theory, combinatorics independent random variables, iterated logarithm, tail probabilities, functions of sums.
Rajarshi Mukherjee, Assistant Professor. Information theoretic limits of statistical problems, adaptive inference of nonparametric functionals, inference in network models, effect of dependence in statistical inference, quasi Monte Carlo methods, statistical genetics, rare variant analyses.
Rasmus Nielsen, Professor. Statistical and computational aspects of evolutionary theory and genetics.
Lior Pachter, Professor. Mathematics, applications of statistics, combinatorics to problems in biology.
Maya Petersen, Assistant Professor.
Elizabeth Purdom, Assistant Professor. Computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics.
Sophia Rabe-Hesketh, Professor. Biostatistics, educational statistics, latent variable models, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models.
+ Steve Selvin, Professor. Public health, biostatistics.
Yun Song, Associate Professor. Computational biology, population genomics, applied probability and statistics.
Terence P. Speed, Professor. Genomics, statistics, genetics and molecular biology, protein sequences.
Mark J. Van Der Laan, Professor. Statistics, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies.
Graduate Group in Biostatistics
101 Haviland Hall