This volume presents Raiffa and Schlaifer's groundbreaking examination of the applications of Bayesian statistical theory to real-life business problems of decision under conditions of uncertainty. The emphasis is on identifying a course of action that is logically consistent with the decision maker's own preference for consequences, as expressed by numerical utilities, and with the weight s/he attaches to unknown variables, as expressed by numerical probabilities. Well-organized with self-contained chapters, suitable for both complete and selected study of topics. Clear outline format and detailed table of contents allows for easy referencing. Extremely useful for its historical value. From the reviews: . "Raiffa and Schlaifer have contributed a major work and a major stimulus to further work. I hope especially that mathematical statisticians will read it and be encouraged to develop the fascinating lines of research that are suggested by it. I recommend it strongly to all statisticians seriously interested in applying statistics to real problems."--ASA Journal. "There is no comparable book. It should have an important effect on the future development of the subject."--Mathematical Reviews.
Applied Statistical Decision Theory
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