# problem_set-9-conditional_prob_decision_trees.pdf - Problem...

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Problem Set 9 Conditional Probability in Decision Trees In this problem set, our exercise is building on what you have learned in prior modules. The three reference videos for probabilistic top-down tree modeling are provided below. Watch each of these videos as they contain important information that supports the remaining work on the problems as well as the final project: Joint Probability Table and Bayes Theorem (14:31) ( ) Conditional Prob and Joint Prob Table in Excel (6:05) ( ) Decision Tree with Conditional Probability (22:00) ( ) Note: Skip the section on EVSI/EVPI and efficiency; we will do diagnostics later. Notes on the videos: You have already learned everything in the first two videos in prior modules. These videos focus on conditional probability in action. In the third video, Professor Wu uses “marginal probabilities.” You may recognize these as weighted probabilities when calculating total probability. However, Prof. Wu then uses a slightly different style of calculating a joint probability matrix. While there should be nothing in here that you have not already seen, the reason this is important is that you are going to use these probabilities to construct a tree diagram for decision making. The main take away is that you need to know how to operationalize the story problem into the components for the tree.