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Making Hard Decisions with Decisiontools Suite
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Table of Contents

1. Introduction to Decision Analysis.
SECTION I: MODELING DECISIONS.
2. Elements of Decision Problems.
3. Structuring Decisions.
4. Making Choices.
5. Sensitivity Analysis.
6. Organizational Decision Making.
SECTION II: MODELING UNCERTAINTY.
7. Probability Basics.
8. Subjective Probability.
9. Theoretical Probability Models.
10. Using Data.
11. Monte Carlo Simulation.
12. Value of Information.
13. Real Options.
SECTION III. MODELING PREFERENCES.
14. Risk Attitudes.
15. Utility Axioms, Paradoxes, and Implications.
16. Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function.
17. Conflicting Objectives II: Multiattribute Utility Models with Interactions
18. Conclusions and Further Reading.

About the Author

Terence Reilly is an associate Professor of Mathematics at Babson College. His interests include developing innovative curriculum for MBA programs, particularly distance programs, along with simulation and decision analysis. His research interests are in developing sensitivity analysis techniques and fitting distribution curves to univariate and multivariate uncertainties. Recently, he has developed courses in financial methods using simulation and decision analysis. Robert T. Clemen is Professor at the Fuqua School of Business at Duke University. He has been an active contributor to the field of decision analysis since earning his Ph.D. at Indiana University in 1984 and is an authority in the use of expert information in decision and risk analysis. He has interests in applying decision analysis in the areas of energy use and corporate sustainabiligy. Aside from his research interests, Bob has a strong focus on making decision analysis understandable to all students at all levels, ranging from high school students to executives.

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1. Introduction to Decision Analysis. SECTION I: MODELING DECISIONS. 2. Elements of Decision Problems. 3. Structuring Decisions. 4. Making Choices. 5. Sensitivity Analysis. 6. Organizational Decision Making. SECTION II: MODELING UNCERTAINTY. 7. Probability Basics. 8. Subjective Probability. 9. Theoretical Probability Models. 10. Using Data. 11. Monte Carlo Simulation. 12. Value of Information. 13. Real Options. SECTION III. MODELING PREFERENCES. 14. Risk Attitudes. 15. Utility Axioms, Paradoxes, and Implications. 16. Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function. 17. Conflicting Objectives II: Multiattribute Utility Models with Interactions 18. Conclusions and Further Reading.

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