Explain the concepts of expected value of sample information and expected value of perfect information.
1. Provide examples of when expected value decision making is appropriate and when it is not. 2. Explain the concepts of expected value of sample information and expected value of perfect information. 3. What are the implications of the “flaw of averages”? 4. Discuss the exponential utility function and its characteristics. 5. What is a risk profile and how can it be used in conjunction with the solution of a decision tree? 6. Explain the concept of utility theory and how utilities can be assessed. 7. What is a decision tree? How is Bayes’s rule useful in implementing a decision tree?
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