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Consider the following decision scenario:  State of Nature  Yes  No  Small $1030 Medium 2040 Med.-Large 3045 Large 4035 Ex-Large 6020\begin{array} {r} { \text { State of Nature } } \\\begin{array} { | l | l | l | } \hline & \text { Yes } & \text { No } \\\hline \text { Small } & \$ 10 ^ { * } & 30 \\\hline \text { Medium } & 20 & 40 \\\hline \text { Med.-Large } & 30 & 45 \\\hline \text { Large } & 40 & 35 \\\hline \text { Ex-Large } & 60 & 20 \\\hline\end{array}\end{array} *PV for profits ($000) The minimax regret strategy would be:


A) small.
B) medium.
C) med.-large.
D) large.
E) ex-large.

F) C) and D)
G) A) and B)

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Which of the following would make decision trees an especially attractive decision-making tool?


A) The need to think through a possible sequence of decisions.
B) The need to maximize the expected value of perfect information.
C) The need to minimize expected regret.
D) The need to avoid suboptimization.
E) The need to minimize costs.

F) A) and B)
G) B) and C)

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Two professors at a nearby university want to coauthor a new textbook in either economics or statistics. They feel that if they write an economics book, they have a 50 percent chance of placing it with a major publisher, and it should ultimately sell about 40,000 copies. If they cannot get a major publisher to take it, then they feel they have an 80 percent chance of placing it with a smaller publisher, with ultimate sales of 30,000 copies. On the other hand, if they write a statistics book, they feel they have a 40 percent chance of placing it with a major publisher, and it should result in ultimate sales of about 50,000 copies. If they cannot get a major publisher to take it, they feel they have a 50 percent chance of placing it with a smaller publisher, with ultimate sales of 35,000 copies. What is the probability that the statistics book would wind up being placed with a smaller publisher?


A) .6
B) .5
C) .4
D) .3
E) 0

F) B) and E)
G) A) and B)

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