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He won the John J. Carty Award for the Advancement of Science from the National Academy of Sciences "for his profound contributions to the theory and practice of statistics, including rigorous foundations for Bayesian inference and trenchant analysis of census adjustment. Freedman was born in Montreal , Quebec , Canada, on 5 March He received a B. He joined the University of California, Berkeley Department of Statistics in as a lecturer and was appointed to the research faculty in He remained at Berkeley his entire career.
Freedman was a consulting or testifying expert on statistics in disputes involving employment discrimination , fair loan practices, voting rights , duplicate signatures on petitions, railroad taxation, ecological inference , flight patterns of golf balls , price scanner errors, bovine spongiform encephalopathy mad cow disease , and sampling.
Freedman and his colleague Kenneth Wachter testified to the United States Congress and the courts against adjusting the and censuses using estimates of differential undercounts. A lawsuit that sought to compel the United States Department of Commerce to adjust the census was heard on appeal by the U.
With David Kaye, Freedman wrote a widely used primer on statistics for lawyers and judges published by the Federal Judicial Center , the education and research agency for the United States federal courts.
In addition to his work in forensic statistics , Freedman had a broad impact on the application of statistics to important medical, social, and public policy issues, such as clinical trials , epidemiology , economic models , and the interpretation of scientific experiments and observational studies. In his applied work, Freedman emphasized exposing and checking the assumptions that underlie standard methods, as well as understanding how those methods behave when the assumptions are false.
He characterized circumstances in which the methods continue to perform well, and those where they break down—regardless of the quality of the data. Two of his earlier results and investigate whether or not and under what circumstances a Bayesian learning approach is consistent, i. In particular the paper with the innocent title "On the asymptotic behaviour of Bayes estimates in the discrete case II" finds the rather disappointing answer that when sampling from a countably infinite population the Bayesian procedure fails almost everywhere, i.
This situation is quite different from the finite case when the discrete random variable takes only finite many values and the Bayesian method is consistent in agreement with earlier findings of Doob Freedman was the author or co-author of articles, 20 technical reports and six books, including a highly innovative and influential introductory statistics textbook, Statistics , with Robert Pisani and Roger Purves, which has gone through four editions.
It is the best introduction to how to think about statistical issues Bibliography[ edit ] David A. Freedman , "On the asymptotic behaviour of Bayes estimates in the discrete case I". The Annals of Mathematical Statistics, vol. David A. Freedman , "On the asymptotic behaviour of Bayes estimates in the discrete case II".
Statistics, 4th Edition
David A. Freedman
Solutions for Statistics