The Department of Statistics: Past and Present
The Department of Statistics of the University was established in 1949 to conduct research into advanced statistics and probability, to work with others in the application of statistics to investigations in the natural and social sciences, and to teach probability and statistical theory and practice on the undergraduate and graduate levels.
From its beginning, the Department has been recognized for the high quality of its faculty and the diversity of its interests. Some of the most important and influential texts and monographs in statistics and probability of the past forty years have been authored by former faculty members of our Department. These include Ergodic Theory and Information, Convergence of Probability Measures, and Probability and Measure 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; and The Foundations of Statistics, a famous analysis of fundamental problems by Leonard J. Savage. Current members of our faculty have written definitive works in a variety of areas of current research interest. These include 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, and Statistics on the Table, accounts by Stephen M. Stigler of the historical development of the field of mathematical statistics; 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. More recent monographs include: Michael J. Wichura’s graduate text, The Coordinate Free Approach to Linear Models; Lars Peter Hansen (with Thomas Sargent) Robustness, an adaptation of robust control techniques to misspecification problems in economics; Kirk Wolter's 2nd edition of his classic Introduction to Variance Estimation; Yali Amit’s 2D Object Detection and Recognition, Models, Algorithms, and Networks, a state-of-the-art account of statistical methods in computer vision; and Greg Lawler's Random Walk: A Modern Introduction.
Faculty members have at various times edited the four leading American or international journals of probability and statistics. Steve Lalley and Greg Lawler were previous editors of the Annals of Probability, the foremost research journal in the theory of probability. Several faculty members have been president of one or both of the two leading societies. Peter McCullagh, a leader in the development of generalized linear models, is a Fellow of the Royal Society. Stephen Stigler served as the President of the International Statistical Institute and was appointed to the Royal Academy of Belgium.