Exam 25: Decision Analysis
Exam 1: What Is Statistics14 Questions
Exam 2: Types of Data, Data Collection and Sampling16 Questions
Exam 3: Graphical Descriptive Methods Nominal Data19 Questions
Exam 4: Graphical Descriptive Techniques Numerical Data64 Questions
Exam 5: Numerical Descriptive Measures147 Questions
Exam 6: Probability106 Questions
Exam 7: Random Variables and Discrete Probability Distributions55 Questions
Exam 8: Continuous Probability Distributions117 Questions
Exam 9: Statistical Inference: Introduction8 Questions
Exam 10: Sampling Distributions65 Questions
Exam 11: Estimation: Describing a Single Population127 Questions
Exam 12: Estimation: Comparing Two Populations22 Questions
Exam 13: Hypothesis Testing: Describing a Single Population129 Questions
Exam 14: Hypothesis Testing: Comparing Two Populations78 Questions
Exam 15: Inference About Population Variances49 Questions
Exam 16: Analysis of Variance115 Questions
Exam 17: Additional Tests for Nominal Data: Chi-Squared Tests110 Questions
Exam 18: Simple Linear Regression and Correlation213 Questions
Exam 19: Multiple Regression121 Questions
Exam 20: Model Building92 Questions
Exam 21: Nonparametric Techniques126 Questions
Exam 22: Statistical Inference: Conclusion103 Questions
Exam 23: Time-Series Analysis and Forecasting145 Questions
Exam 24: Index Numbers25 Questions
Exam 25: Decision Analysis51 Questions
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In decision analysis, the alternatives are referred to as events and the states of nature are referred to as acts.
(True/False)
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An opportunity loss is the difference between what the decision maker's profit for an act (alternative) is and what the profit could have been had the best decision been made.
(True/False)
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Since the expected monetary value decision is always the same as the expected opportunity loss decision, then EMV*( ) = EOL*( ), for any alternative .
(True/False)
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The expected payoff with perfect information (EPPI) represents the maximum amount a decision maker would be willing to pay for perfect information.
(True/False)
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The expected value of perfect information (EVPI) is the difference between the expected payoff with perfect information (EPPI) and the expected monetary value (EMV*). That is,
EVPI = EPPI - EMV*.
(True/False)
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A payoff table lists the monetary values for each possible combination of:
(Multiple Choice)
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The objective of a preposterior analysis is to determine whether the value of the prediction is greater or less than the cost of the information.
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Salaries for employees would be considered a state of nature for a business firm.
(True/False)
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In making decisions, we choose the decision with the smallest expected monetary value, or the largest expected opportunity loss.
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We can use the payoff table to calculate the expected monetary value (EMV) and the expected opportunity loss (EOL) of each act (alternative).
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Which of the following would not be considered a state of nature for a business firm?
(Multiple Choice)
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Which of the following best describes the expected value of sample information (EVSI)?
(Multiple Choice)
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The following table displays the payoffs (in thousands of dollars) for five different decision alternatives under three possible states of nature: Alternative State of Nature \ 100 \ 80 \ 35 \ 20 \ 0 \ 70 \ 75 \ 55 \ 50 \ 15 -\ 30 \ 0 \ 35 \ 55 \ 60
The prior probabilities of the states of nature are:
P( ) = 0.2, P( ) = 0.3, P( ) = 0.5
a. Calculate the expected monetary value for each alternative with present information. What decision should be made using the EMV criterion?
b. Calculate the expected payoff with perfect information.
c. Calculate the expected value of perfect information.
d. Convert the payoff table to an opportunity loss table.
e. Calculate the expected opportunity loss for each act with present information. What decision should be made using the EOL criterion?
(Essay)
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If EOL( ) = $13 000, EOL( ) = $25 000 and EOL( ) = $20 000, then EOL* = $25 000.
(True/False)
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Worker safety laws would be considered a state of nature for a business firm.
(True/False)
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In general, the branches of a decision tree represent stages of events.
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