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Operations Research Decision Analysis

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Decision Analysis: Model#1-Decision Trees with Conditional Probability

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1. Question 1: A decision tree is primarily used to:
A) Minimize total costs in a decision-making process B) Graphically represent decision alternatives, probabilities, and outcomes C) Identify the highest possible payoff in a decision D) Calculate the expected utility of all outcomes
2. Question 2: In decision trees, conditional probability refers to:
A) The likelihood of an event occurring regardless of prior outcomes B) The likelihood of an event occurring given that another event has already occurred C) The average probability of all possible outcomes D) The maximum payoff given any decision
3. Question 3: When calculating expected value in a decision tree with conditional probabilities, which of the following steps is correct?
A) Multiply the probability of each outcome by the total number of outcomes B) Multiply the payoff of each outcome by its conditional probability and sum them C) Add up all the payoffs and divide by the number of outcomes D) Use only the payoffs of the most likely outcomes to compute the expected value
4. Question 4: Which of the following best describes a chance node in a decision tree?
A) A point where the decision maker must choose an alternative B) A point where the payoff from a decision is calculated C) A point where probabilities are assigned to possible future events D) A point where marginal costs and marginal benefits are equal
5. Question 5: In a decision tree, Bayes' Theorem is often used to:
A) Update the probability of a decision based on new information B) Maximize the payoff for each alternative decision C) Identify the most profitable branch of the tree D) Assign equal probabilities to all outcomes