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Synopsis
In real-life decision-making situations it is necessary to make decisions with incomplete information, for oftentimes uncertain results. In Decision-Making Under Uncertainty, Dr. Chacko applies his years of statistical research and experience to the analysis of twenty-four real-life decision-making situations, both those with few data points (eg: Cuban Missile Crisis), and many data points (eg: aspirin for heart attack prevention). These situations encompass decision-making in a variety of business, social and political, physical and biological, and military environments. Though different, all of these have one characteristic in common: their outcomes are uncertain/unkown, and unknowable. Chacko Demonstrates how the decision-maker can reduce uncertainty by choosing probable outcomes using the statistical methods he introduces.
This detailed volume develops standard statistical concepts (t, x2, normal distribution, ANOVA), and the less familiar concepts (logical probability, subjective probability, Bayesian Inference, Penalty for Non-Fulfillment, Bluff-Threats Matrix, etc.). Chacko also offers a thorough discussion of the underlying theoretical principles. The end of each chapter contains a set of questions, three quarters of which focus on concepts, formulation, conclusion, resource commitments, and caveats; only one quarter with computations. Ideal for the practitioner, the work is also designed to serve as the primary text for graduate or advanced undergraduate courses in statistics and decision science.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
GEORGE K. CHACKO is Professor of Systems Science at the University of Southern California, and formerly the manager of operations research at Hughes Semiconductor Division. His previous works include Technology Management (Praeger 1988) and Dynamic Program Management (Praeger 1989).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Decision-Making under Uncertainty : An Applied Statistics Approach
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Bloomsbury Publishing USA, 1990
ISBN 10 : 0275935698
ISBN 13 : 9780275935696
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Decision-Making Under Uncertainty: An Applied Statistics Approach
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Decision-Making Under Uncertainty: An Applied Statistics Approach
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ISBN 13 : 9780275935696
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Etat : New. It is often necessary to make decisions with incomplete information. In this work, the author applies his statistical research experience to the analysis of 24 decision-making situations, demonstrating how decision-makers can reduce uncertainty by using the statistical methods he introduces. Num Pages: 272 pages, bibliography, index. BIC Classification: KJM; PBT. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 230. Weight in Grams: 635. . 1990. hardcover. . . . . N° de réf. du vendeur V9780275935696
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Decision-Making under Uncertainty (Hardcover)
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Hardcover. Etat : new. Hardcover. In real-life decision-making situations it is necessary to make decisions with incomplete information, for oftentimes uncertain results. In Decision-Making Under Uncertainty, Dr. Chacko applies his years of statistical research and experience to the analysis of twenty-four real-life decision-making situations, both those with few data points (eg: Cuban Missile Crisis), and many data points (eg: aspirin for heart attack prevention). These situations encompass decision-making in a variety of business, social and political, physical and biological, and military environments. Though different, all of these have one characteristic in common: their outcomes are uncertain/unkown, and unknowable. Chacko Demonstrates how the decision-maker can reduce uncertainty by choosing probable outcomes using the statistical methods he introduces.This detailed volume develops standard statistical concepts (t, x2, normal distribution, ANOVA), and the less familiar concepts (logical probability, subjective probability, Bayesian Inference, Penalty for Non-Fulfillment, Bluff-Threats Matrix, etc.). Chacko also offers a thorough discussion of the underlying theoretical principles. The end of each chapter contains a set of questions, three quarters of which focus on concepts, formulation, conclusion, resource commitments, and caveats; only one quarter with computations. Ideal for the practitioner, the work is also designed to serve as the primary text for graduate or advanced undergraduate courses in statistics and decision science. It is often necessary to make decisions with incomplete information. In this work, the author applies his statistical research experience to the analysis of 24 decision-making situations, demonstrating how decision-makers can reduce uncertainty by using the statistical methods he introduces. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780275935696
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Etat : New. It is often necessary to make decisions with incomplete information. In this work, the author applies his statistical research experience to the analysis of 24 decision-making situations, demonstrating how decision-makers can reduce uncertainty by using the statistical methods he introduces. Num Pages: 272 pages, bibliography, index. BIC Classification: KJM; PBT. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 230. Weight in Grams: 635. . 1990. hardcover. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9780275935696
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