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Elementary Bayesian statistics / the late Gordon Antelman, (formerly Professor of Statistics, University of Chicago, US.) ; edited by Albert Madansky, (HGB Alexander Professor of Business Administration) and Robert McCulloch, (Professor of Econometrics and Statistics, University of Chicago, US)
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Cheltenham, UK ; Northampton, MA : Edward Elgar Publishing, 1997Description: 1 Online-Ressource (xv, 459 pages) : illustrationsISBN:- 9781035335145
- 519.5/42 21
- QA279.5
Contents:
Summary: Elementary Bayesian Statistics is a thorough and easily accessible introduction to the theory and practical application of Bayesian statistics. It presents methods to assist in the collection, summary and presentation of numerical data. Bayesian statistics are becoming an increasingly important and more frequently used method for analysing statistical data. The author defines concepts and methods with a variety of examples and uses a stage-by-stage approach to coach the reader through the applied examples. Also included are a wide range of problems to challenge the reader and the book makes extensive use of Minitab to apply computational techniques to statistical problems. Issues covered include probability, Bayes's Theorem and categorical states, frequency, the Bernoulli process and Poisson process, estimation, testing hypotheses and the normal process with known parameters and uncertain parameters. Elementary Bayesian Statistics will be an essential resource for students as a supplementary text in traditional statistics courses. It will also be welcomed by academics, researchers and econometricians wishing to know more about Bayesian statisticsPPN: PPN: 1922107441Package identifier: Produktsigel: ZDB-1-EWE | ZDB-77-EEC | ZDB-77-ECE
Contents: Foreword -- 1. Introduction: Statistics and probability -- 2. Some basic probability -- 3. More basic probability -- 4. Bayes' theorem, categorical states -- 5. Bernoulli process, parameter known -- 6. Bernoulli and bayes -- 7. Poisson process, parameter known -- 8. Poisson and bayes -- 9. Normal process, known parameters -- 10. Normal process, uncertain parameters -- 11. Estimation -- 12. Testing hypotheses -- Appendix -- References -- Index.
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