Alternatives 1 and 2 in the following payoff table represent the two possible manufacturing strategies that the EKA manufacturing company can adopt. The level of demand affects the success of both strategies. The states of nature (S_I) represent the levels of demand for the company products. S₁, S₂, and S₃ characterize high, medium, and low demand, respectively. The payoff values are in thousands of dollars.
The management believes that weather conditions significantly affect the level of demand. 48 monthly sales reports are randomly selected. These monthly sales reports show 15 months with high demand, 28 months with medium demand, and 5 months with low demand. 12 of the 15 months with high demand had favorable weather conditions. 14 of the 28 months with medium demand had favorable weather conditions. Only 1 of the 5 months with low demand had favorable weather conditions. Based on this information, the prior probabilities have been revised. If the weather conditions are favorable, P(S₁) = .4286, P(S₂) = .5357, and P(S₃) = .0357; and if the weather conditions are poor, P(S₁) = .1364, P(S₂) = .6818, and P(S₃) = .1818. It is also determined that the probability of favorable weather is .56 and the probability of poor weather is .44.
Determine the expected value of sample information. What is the maximum amount that the company is willing to pay for the weather information and the additional analysis?

Question

Alternatives 1 and 2 in the following payoff table represent the two possible manufacturing strategies that the EKA manufacturing company can adopt. The level of demand affects the success of both strategies. The states of nature (S_I) represent the levels of demand for the company products. S₁, S₂, and S₃ characterize high, medium, and low demand, respectively. The payoff values are in thousands of dollars.

The management believes that weather conditions significantly affect the level of demand. 48 monthly sales reports are randomly selected. These monthly sales reports show 15 months with high demand, 28 months with medium demand, and 5 months with low demand. 12 of the 15 months with high demand had favorable weather conditions. 14 of the 28 months with medium demand had favorable weather conditions. Only 1 of the 5 months with low demand had favorable weather conditions. Based on this information, the prior probabilities have been revised. If the weather conditions are favorable, P(S₁) = .4286, P(S₂) = .5357, and P(S₃) = .0357; and if the weather conditions are poor, P(S₁) = .1364, P(S₂) = .6818, and P(S₃) = .1818. It is also determined that the probability of favorable weather is .56 and the probability of poor weather is .44.
Determine the expected value of sample information. What is the maximum amount that the company is willing to pay for the weather information and the additional analysis?

Quizplus · Accepted Answer

The Answer of Alternatives 1 and 2 in the following payoff table represent the two possible manufacturing strategies that the EKA manufacturing company can adopt. The level of demand affects the success of both strategies. The states of nature (S_I) represent the levels of demand for the company products. S₁, S₂, and S₃ characterize high, medium, and low demand, respectively. The payoff values are in thousands of dollars. The management believes that weather conditions significantly affect the level of demand. 48 monthly sales reports are randomly selected. These monthly sales reports show 15 months with high demand, 28 months with medium demand, and 5 months with low demand. 12 of the 15 months with high demand had favorable weather conditions. 14 of the 28 months with medium demand had favorable weather conditions. Only 1 of the 5 months with low demand had favorable weather conditions. Based on this information, the prior probabilities have been revised. If the weather conditions are favorable, P(S₁) = .4286, P(S₂) = .5357, and P(S₃) = .0357; and if the weather conditions are poor, P(S₁) = .1364, P(S₂) = .6818, and P(S₃) = .1818. It is also determined that the probability of favorable weather is .56 and the probability of poor weather is .44. Determine the expected value of sample information. What is the maximum amount that the company is willing to pay for the weather information and the additional analysis?

Alternatives 1 and 2 in the Following Payoff Table Represent