# Question: Consider two weighted coins Coin 1 has a probability of

Consider two weighted coins. Coin 1 has a probability of 0.3 of turning up heads, and coin 2 has a probability of 0.6 of turning up heads. A coin is tossed once; the probability that coin 1 is tossed is 0.6, and the probability that coin 2 is tossed is 0.4. The decision maker uses Bayes’ decision rule to decide which coin is tossed. The payoff table is as follows:

(a) What is the optimal alternative before the coin is tossed?

(b) What is the optimal alternative after the coin is tossed if the outcome is heads? If it is tails?

(a) What is the optimal alternative before the coin is tossed?

(b) What is the optimal alternative after the coin is tossed if the outcome is heads? If it is tails?

## Answer to relevant Questions

There are two biased coins with probabilities of landing heads of 0.8 and 0.4, respectively. One coin is chosen at random (each with probability 1/2) to be tossed twice. You are to receive $100 if you correctly predict how ...Using Bayes’ decision rule, consider the decision analysis problem having the following payoff table (in units of thousands of dollars): (a) Which alternative should be chosen? What is the resulting expected payoff? (b) ...You are given the decision tree below, where the numbers in parentheses are probabilities and the numbers on the far right are payoffs at these terminal points. Analyze this decision tree to obtain the optimal policy. Use the scenario given in Prob.16.3-13. (a) Draw and properly label the decision tree. Include all the payoffs but not the probabilities. (b) Find the probabilities for the branches emanating from the event nodes. (c) Apply ...The Morton Ward Company is considering the introduction of a new product that is believed to have a 50-50 chance of being successful. One option is to try out the product in a test market, at a cost of $5 million, before ...Post your question