1. Explain why in decision analysis we are concerned with the expected value of information.
2. Calculate the EVPI for the decision shown in Figure 12.9.
3. What is the EVPI for the decision shown in Figure 12.10? Must you perform any calcu lations? Can you draw any conclusions regarding the relationship between value of in formation and deterministic dominance?
4. For the decision tree in Figure 12.11, assume Chance Events E and F are independent. +
a. Draw the appropriate decision tree and calculate the EVPI for Chance Event E only.
b. Draw the appropriate decision tree and calculate the EVPI for Chance Event F only.
c. Draw the appropriate decision tree and calculate the EVPI for both Chance Events E and F: that is, perfect information for both E and F is available before a decision is made.