Lecture Business statistics in practice (7/e): Chapter 19 - Bowerman, O'Connell, Murphree

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Chapter 19 - Decision theory. After studying this chapter you will be able to: Make decisions under uncertainty and under risk and assess the value of perfect information, make decisions using posterior analysis and assess the value of sample information, make decisions using utility theory.

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Nội dung Text: Lecture Business statistics in practice (7/e): Chapter 19 - Bowerman, O'Connell, Murphree

Chapter 19 Decision Theory McGrawHill/Irwin Copyright © 2014 by The McGrawHill Companies, Inc. All rights reserved.
Decision Theory 19.1 Introduction to Decision Theory 19.2 Decision Making Using Posterior Probabilities 19.3 Introduction to Utility Theory 192
LO19-1: Make decisions under uncertainty and under risk and assess 19.1 Introduction to Decision Theory the value of perfect information. States of nature: A set of potential future conditions that affects decision results Alternatives: A set of alternative actions for the decision maker to chose from Payoffs: A set of payoffs for each alternative under each potential state of nature 193
LO19-1 Decision Making Under Uncertainty  Maximin: Identify the minimum (or worst) possible payoff for each alternative and select the alternative that maximizes the worst possible payoff (Pessimistic)  Maximax: Identify the maximum (or best) possible payoff for each alternative and select the alternative that maximizes the best possible payoff (Optimistic)  Expected value criterion: Using prior probabilities for the states of nature, compute the expected payoff for each alternative and select the alternative with the largest expected payoff 194
LO19-2: Make decisions using posterior analysis and assess the value of sample information. 19.2 Decision Making Using Posterior Probabilities When we use expected value to choose the best alternative, we call this prior decision analysis Often, sample information can be obtained to help us make a better decision In this case, we compute expected values by using posterior probabilities We call this posterior decision analysis 195
LO19-2 Bayes’ Theorem Calculations 196
LO19-3: Make decisions using utility theory. 19.3 Introduction to Utility Theory Utilities are measures of the relative value of varying dollar payoffs for an individual decision maker and thus capture the decision maker’s attitude toward risk Under certain mild assumptions about rational behavior, decision makers should replace dollar payoffs with their respective utilities and maximize expected utility 197
LO19-3 Introduction to Utility Theory 198