A company is facing three types of decisions for the purchasing of a seasonal product. The pro t projection may depend on the demand level. The payo s for the situations are given in the following table: Demand Decision High (s1) Medium (s2) Low (s3) d1 60 60 50 d2 80 80 30 d3 100 70 10 1. If the prior probabilities are 0.3, 0.3, and 0.4, respectively, what is the recommended decision? Show all the calculations and answer with a decision tree. 2. At each preseason sales meeting, the vice president of sales provides a personal opinion re- garding potential demand for the product. The prediction of the vice president have always been either excellent (E) or very good (G). Posterior probabilities are as follows. P(V)=0.7; P(E)=0.3 P(s1jE)=0.34; P(s1jV)=0.2 P(s2jE)=0.32; P(s2jV)=0.26; 1 ) Suppose that the prior probability of low demand is always fixed to 0.4, give a sensitivity analysis on the other probabilities and give different scenarios with a graphic.
A company is facing three types of decisions for the purchasing of a seasonal product. The pro t
projection may depend on the demand level. The payo s for the situations are given in the following
table:
Demand
Decision High (s1) Medium (s2) Low (s3)
d1 60 60 50
d2 80 80 30
d3 100 70 10
1. If the prior probabilities are 0.3, 0.3, and 0.4, respectively, what is the recommended decision?
Show all the calculations and answer with a decision tree.
2. At each preseason sales meeting, the vice president of sales provides a personal opinion re-
garding potential demand for the product. The prediction of the vice president have always
been either excellent (E) or very good (G). Posterior probabilities are as follows.
P(V)=0.7; P(E)=0.3
P(s1jE)=0.34; P(s1jV)=0.2
P(s2jE)=0.32; P(s2jV)=0.26;
1 ) Suppose that the prior probability of low demand is always fixed to 0.4, give a sensitivity
analysis on the other probabilities and give different scenarios with a graphic.
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