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Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis
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Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis in Bloomington, MN
Current price: $150.00
Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis in Bloomington, MN
Current price: $150.00
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Size: Hardcover
Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis
provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory.
Features
Covers approaches for making decisions under certainty, risk, and uncertainty
Illustrates expected utility theory and its extensions
Describes approaches to elicit the utility function
Reviews classical and Bayesian approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision theory
provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory.
Features
Covers approaches for making decisions under certainty, risk, and uncertainty
Illustrates expected utility theory and its extensions
Describes approaches to elicit the utility function
Reviews classical and Bayesian approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision theory
Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis
provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory.
Features
Covers approaches for making decisions under certainty, risk, and uncertainty
Illustrates expected utility theory and its extensions
Describes approaches to elicit the utility function
Reviews classical and Bayesian approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision theory
provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory.
Features
Covers approaches for making decisions under certainty, risk, and uncertainty
Illustrates expected utility theory and its extensions
Describes approaches to elicit the utility function
Reviews classical and Bayesian approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision theory
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