Chairman's Introduction, Michael Stein | Faculty Research Summaries

The Department of Statistics of the University was established in 1949 to conduct research into probability and statistical theory, to work with others in the application of statistics to investigations in the natural and social sciences, and to teach statistical theory and practice on the undergraduate and graduate levels. From the beginning, the Department has been known for the high quality of its faculty and the diversity of its interests. This is well illustrated by books written by current and former members: Ergodic Theory and Information, Convergence of Probability Measures, and Probability and Measure, three mathematically oriented probability texts by Patrick Billingsley; Inference and Disputed Authorship: The Federalist, an application of Bayesian methods to fix the authorship of the Federalist Papers, by David L. Wallace and Frederick Mosteller; The Foundations of Statistics, a famous analysis of fundamental problems by Leonard J. Savage; Measures of Association for Cross Classifications, a collection of influential work on statistical methods important in social science and elsewhere by Leo A. Goodman and William H. Kruskal; Generalized Linear Models, an influential monograph that extends the scope of linear models greatly, including to models for discrete data, by Peter McCullagh and John Nelder; Tensor Methods in Statistics, a monograph on methods for making complex multivariate calculations, by Peter McCullagh; Elements of Statistical Computing: Numerical Computation, a far-ranging text on numerical methods for statistics by Ronald A. Thisted; The History of Statistics: The Measurement of Uncertainty Before 1900, an account by Stephen M. Stigler of the historical development of the field of mathematical statistics, and Interpolation of Spatial Data: Some Theory for Kriging, a monograph providing a sound mathematical basis for understanding the behavior of a popular methodology for prediction of spatial processes by Michael L. Stein.

Faculty members have contributed many statistical articles to books and journals in theoretical and applied statistics, biophysics, chemistry, mathematics, geophysics, astronomy, bacteriology, biometry, public health, computer science, imaging, psychology, sociology, medicine, law, and business. Members of the department have at various times edited the three leading American journals of probability and statistics and several have been president of one or both of the two leading societies. In addition to editing the statistics articles for the International Encyclopedia of the Social Sciences, William Kruskal has served on many private and government committees concerned with statistics and public affairs. Peter McCullagh, a leader in the development of generalized linear models, is a Fellow of the Royal Society. Michael Stein, a leading expert in spatial statistics, works on environmental and cosmological applications. Per Mykland uses his expertise in martingale theory and stochastic calculus to better understand financial markets. Yali Amit is developing fundamentally new approaches to object recognition and computer vision. Xiao-Li Meng has made major contributions to a number of areas in statistical computing, from the EM algorithm to Markov chain Monte Carlo methods.

Faculty Research Summaries