This question is taken from the 6th Edition, NOT the 5th edition. The answer alr

Question

This question is taken from the 6th Edition, NOT the 5th edition. The answer already provided for the 5th edition is incorrect. I have already went over it. Please use the table below for the values to be considered.

3000

In the above example (Example 6.2), Acme's probability of technological success, 0.8, is evidently large enough to make "continue development" the best decision. How low would this probability have to be to make the opposite decision best?

Decision 1 Decision 2 Decision 3 Payoff/Cost Probability Payoff/Cost Probability Payoff/Cost Probability 50,000 0.1 5,000 0.8 3,000 1 10,000 0.2 -1,000 0.2 -5,000 0.7 EMV 3500 EMV 3800 EMV

3000

Explanation / Answer

Suppose let us assume that Research predicts 40% success correctly when there was a technological success. But 60% predicts a failure when there was successes.

Using Bayes' theorem to revise the probability of the success and failure.

In the decision 2, P(S) is 0.80 is too large, because the underlieing assumption of the research predicts somehow eradically with the assumed probability of P(RS)=0.4 and P(RF)=0.6. Joint probability is the multiplication of Research predicted conditional probability and the decision probabilities of success and failure. Then sum the joint probability and use the sum to divide the joint probabilities to get the revised probabilities for the decision 2. so that the next better decision 1 will be the best choice conditionally.

To the revise the probabilities, we have to use Bayes' theorem, with the conditional probabilities. How successful the research method in arriving at the probability of 0.8 and 0.2 are the criteria that are used conditionally here. Since the problem stated too large is not a measurable evidence, so the research prediction assumptions are used to solve the problem here.

Probability Research predicts Joint Probability Revised Probability Technological success P(S) 0.8 0.4 0.32 0.73 Technological failure P(F) 0.2 0.6 0.12 0.27 0.44

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