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Chapter 13
Decision Analysis
13.1 Problem Formulation 13.5 Decision Analysis with Sample Information
Payoff Tables Decision Tree
Decision Trees Decision Strategy
Risk Profile
13.2 Decision Making without Probabilities
Expected Value of Sample Information
Optimistic Approach
Efficiency of Sample Information
Conservative Approach
Minimax Regret Approach 13.6 Calculating Branch Probabilities
13.3 Decision Making with Probabilities 13.7 Utility and Decision Making
Expected Value of Perfect Information The Meaning of Utility
Developing Utilities for Payoffs
13.4 Risk Analysis and Sensitivity Analysis
Expected Utility Approach
Risk Analysis
Sensitivity Analysis
Learning Objectives By the end of this chapter you will be able to:
l Calculate and explain expected value
l Construct and explain a decision tree
l Evaluate the value of perfect information
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