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The 16th Annual Charles R. DePrima Memorial Bradley Efron BASEBALL, SHAKESPEARE, AND MODERN STATISTICAL THEORY Abstract: Statistics is the mathematical theory of learning from experience, especially experience that arrives a little bit at a time: a baseball player's success or failure in one trip to the plate, a cancer patient's survival or death in a clinical trial of a new treatment. Two competing schools, the Bayesians and the frequentists, have contended for supremacy in information collection for two and a half centuries. Suddenly, at the beginning of the TwentyFirst Century, new scientific technology, producing torrents of data asking volumes of questions, has forced a combined Bayesian/frequentist approach to information analysis. I'll describe both the old and new theories through a few examples. No background beyond elementary probability will be assumed. Bradley Efron is Professor of Statistics and Biostatistics at Brad was a Caltech math major and president of Ricketts House, graduating in 1960. For his Ph.D. in statistics he went to Stanford, which has been his academic home ever since. At Stanford he has been chair of the Statistics Department, Associate Dean of Science, and chair of the Faculty Senate. He is a past president of the American Statistical Association, a MacArthur Prize winner, and a member of the National Academy of Sciences.
The Charles R. DePrima Memorial Undergraduate Mathematics Lecture was established by a gift from Charles R. DePrima and Margaret Thurmond DePrima. The Institute is privileged to honor the memory of Professor DePrima and his distinguished contribution to mathematics and Caltech, where he served as a faculty member for over forty years, with a lecture each year by an outstanding mathematician. Professor DePrima perceived that there were few or no special talks or seminars designed for undergraduates; he and Margaret DePrima intended that this lecture series would fill that need. 
