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This is the preliminary program for the 2006 Joint Statistical
Meetings in Seattle, Washington.
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The views expressed here are those of the individual authors and not necessarily those of the ASA or its board, officers, or staff. Back to main JSM 2006 Program page |
= Applied Session,
= Theme Session,
= Presenter, Sheraton Seattle Hotel & Towers = “S”| CE_04C | Sat, 8/5/06, 8:30 AM - 5:00 PM | CC-306 |
| Bayesian Inference - Continuing Education - Course | ||
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The ASA, Section on Bayesian Statistical Science |
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| Instructor(s): Bruno Sanso, University of California, Santa Cruz | ||
| This course will review the bases of Bayesian inference. It will start by presenting the basic elements of statistical inference that use likelihood functions. We will then consider specifying prior distributions, describe tools for both pointwise and interval estimation and prediction, present the Bayesian theory of hypothesis testing and model comparison, and review the elements of modern computational methods used in the applications of Bayesian models. The course will target students or professionals with a good knowledge of statistics who want to learn or refresh their knowledge of basic Bayesian inference. The level of mathematical sophistication will be kept as low as possible, but calculus and basic probability theory are considered prerequisite. RECOMMENDED TEXTBOOK: Migon, H.S. and Gamerman, D. (1999). Statistical Inference: An Integrated Approach. Oxford University Press. ISBN: 0340740590. | ||
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JSM 2006
For information, contact jsm@amstat.org
or phone (888) 231-3473. If you have questions about the Continuing Education program,
please contact the Education Department. |