Last edited by Magore
Monday, August 3, 2020 | History

5 edition of Applied statistical decision theory found in the catalog.

Applied statistical decision theory

by Howard Raiffa

  • 227 Want to read
  • 19 Currently reading

Published by M.I.T. Press in Cambridge, Mass .
Written in English

    Subjects:
  • Statistical decision.

  • Edition Notes

    Bibliographical footnotes.

    Statement[by] Howard Raiffa and Robert Schlaifer.
    ContributionsSchlaifer, Robert, joint author.
    Classifications
    LC ClassificationsQA279.4 .R34 1968
    The Physical Object
    Paginationxxviii, 356 p.
    Number of Pages356
    ID Numbers
    Open LibraryOL5616964M
    LC Control Number68025380

    Statistical Decision Theory and Related Topics II is a compendium of papers presented at an international symposium on Statistical Decision Theory and Related Topics held at Purdue University in May, The researchers invited to participate, and to author papers for this volume, are among the leaders in the field of Statistical Decision Theory. Applied statistical decision theory: Author: SCHLAIFER, Robert; RAIFFA, Howard: Abstract: In general, this book is concerned with capital budgeting and decision theory. Specifically, it centers around a singular uncertainty decision - the decision by oil and gas operators to drill, or not to drill, a well.

    The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches. Decision analysis, also called statistical decision theory, involves procedures for choosing optimal decisions in the face of uncertainty. In the simplest situation, a decision maker must choose the best decision from a finite set of alternatives when there are two or more possible.

    These are the books that I've found helpful. This is by no means a complete list--and in particular, I'm not trying to cover anything beyond the core topics--but it is a solid start. As always, my recommendations tell you as much about my biases. Although intended to communicate the relevance, feasibility and value of decision theory for ‘everyday’ (statistical) professionals, the book can also be of value as a reference in a graduate course in statistics.” (Heleno Bolfarine, Mathematical Reviews, September, ).


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Applied statistical decision theory by Howard Raiffa Download PDF EPUB FB2

In the field of statistical decision theory Professors Raiffa and Schlaifer have sought to develop new analytical tech­ niques by which the modern theory of utility and subjective probability can actu­ ally be applied to the economic analysis of typical sampling problems.

This book, the first in a group entitled Studies in Managerial. Applied Statistical Decision Theory 1st Edition. by Howard Raiffa (Author) › Visit Amazon's Howard Raiffa Page. Find all the books, read about the author, and more. See search results for this author. Are you an author.

Learn about Author Central. Howard Raiffa Cited by: Applied Statistical Decision Theory by Howard; Schlaifer, Robert Raiffa and a great selection of related books, art and collectibles available now at vassilyk.com Applied Statistical Decision Theory book.

Read reviews from world’s largest community for readers.4/5. Note: Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study. The specific requirements or preferences of your reviewing publisher, classroom teacher, institution or organization should be applied.

Jan 25,  · Unlike most introductory texts in statistics, Introduction to Statistical Decision Theory integrates statistical inference with decision making and discusses real-world actions involving economic payoffs and risks. After developing the rationale and demonstrating the power and relevance of the subjective, decision approach, the text also Cited by: Robert O.

Schlaifer (13 September – 24 July ) was a pioneer of Bayesian decision vassilyk.com the time of his death he was William Ziegler Professor of Business Administration Emeritus of the Harvard Business vassilyk.com he was elected as a Fellow of the American Statistical Association.

Robert Osher Schlaifer, a native of Vermillion, S.D. and a graduate of Amherst College, had a. "In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems." --From the foreword to their classic work "Applied Statistical Decision Theory," First published in the s through Harvard University.

In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems. —From the foreword to their classic work Applied Statistical Decision Theory.

First published in the s through Harvard University and. Jun 02,  · "In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems." —From the foreword to their classic work Applied Statistical Decision Theory.

First published in the s through Harvard University. Jun 02,  · Applied Statistical Decision Theory by Howard Raiffa,available at Book Depository with free delivery worldwide.4/5(6).

I wanted a book which discussed the more theoretical ideas and techniques of decision theory, but in a manner that was constantly oriented towards solving statistical problems. In particular, it seemed crucial to include a discussion of when and why the various decision prin­ ciples should be used, and indeed why decision theory is needed at vassilyk.com: James O.

Berger. Decision theory (or the theory of choice not to be confused with choice theory) is the study of an agent's choices. Decision theory can be broken into two branches: normative decision theory, which analyzes the outcomes of decisions or determines the optimal decisions given constraints and assumptions, and descriptive decision theory, which analyzes how agents actually make the decisions they do.

Jan 01,  · "In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems."—From the foreword to Pages: Book Description.

Instructs readers on how to use methods of statistics and experimental design with R software. Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in.

I wanted a book which discussed the more theoretical ideas and techniques of decision theory, but in a manner that was constantly oriented towards solving statistical problems. In particular, it seemed crucial to include a discussion of when and why the various decision prin­ ciples should be used, and indeed why decision theory is needed at all.

Nov 02,  · Statistical decision theory has been applied to the treatment planning decision of radiation therapy. The decision involves the choice of parameters which determine the radiation dose distribution. To choose among dose distributions requires a decision Author: T.

Schultheiss, Anas M. El-Mahdi. Instructs readers on how to use methods of statistics and experimental design with R software. Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research.

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields.

With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.

Applied statistical decision theory by Raiffa, Howard, ; Schlaifer, Robert, joint author. Publication date Topics Statistical decision Publisher Cambridge, Mass., M.I.T. Press Borrow this book to access EPUB and PDF files. IN COLLECTIONS.

Books to Borrow. Books for People with Print Disabilities. Internet Archive vassilyk.com:. The Bayesian revolution in statistics—where statistics is integrated with decision making in areas such as management, public policy, engineering, and clinical medicine—is here to stay.

Introduction to Statistical Decision Theory states the case and in a self-contained, comprehensive way shows how the approach is operational and relevant for real-world decision making under uncertainty.Abstract.

Decision theory is the science of making optimal decisions in the face of uncertainty. Statistical decision theory is concerned with the making of decisions when in the presence of statistical knowledge (data) which sheds light on some of the uncertainties involved in the decision vassilyk.com by: Axiomatic foundations of expected utility; coherence and the axioms of probability (the Dutch Book theorem).

Elicitation of probabilities and utilities. The value of information. Estimation and hypothesis testing as decision problems: risk, sufficiency, completeness and admissibility. Stein estimation. Bayes decision functions and their properties.