Yahoo Web Search

Search results

  1. David Amiel Freedman (5 March 1938 – 17 October 2008) was a Professor of Statistics at the University of California, Berkeley. He was a distinguished mathematical statistician whose wide-ranging research included the analysis of martingale inequalities, Markov processes , de Finetti's theorem , consistency of Bayes estimators , sampling , the ...

  2. David A. Freedman was Professor of Statistics at the University of California, Berkeley. He also taught in Athens, Caracas, Jerusalem, Kuwait, London, and Mexico City. He is the author of several books, including a widely-used elementary text.

  3. Jan 9, 2020 · Im a science journalist and author. Im a contributing writer at The Atlantic, where I’ve had several cover stories, and semi-regular cover-story contributor to Newsweek . I’ve contributed off and on to a number of publications, including Scientific American, Politico, Quanta, Men’s Journal, and others. I’m the author of five books.

  4. David Freedman (April 26, 1898 – December 8, 1936) (aged 38) was a Romanian-born American playwright and biographer who became known as the "King of the Gag-writers" in the early days of radio. Biography. David Freedman was born in Botoşani, Romania, as the first child and only son of Sara and Israel Freedman.

  5. David A. Freedman is a professor of statistics at U. C. Berkeley and a member of the American Academy of Arts and Sciences. He has written several books and papers on probability, statistics, and law, and has consulted for various government agencies and testified as an expert witness.

  6. Oct 20, 2008 · BERKELEY — David A. Freedman, a professor of statistics at the University of California, Berkeley, who fought for three decades to keep the United States census on a firm statistical foundation, died Friday, Oct. 17, of bone cancer at his home in Berkeley. He was 70.

  7. Jul 10, 2024 · David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy, law, and epidemiology.