Preface | p. xxi |
Introduction to Decision Analysis | p. 1 |
Gypsy Moths and the Oda | p. 1 |
Why Are Decisions Hard? | p. 2 |
Why Study Decision Analysis? | p. 3 |
Subjective Judgments and Decision Making | p. 5 |
The Decision-Analysis Process | p. 5 |
Where Is Decision Analysis Used? | p. 8 |
Where Does the Software Fit In? | p. 9 |
Where Are We Going from Here? | p. 11 |
Modeling Decisions | p. 19 |
Elements of Decision Problems | p. 21 |
Values and Objectives | p. 21 |
Making Money: A Special Objective | p. 22 |
Values and the Current Decision Context | p. 23 |
Boeing's Supercomputer | p. 24 |
Decisions to Make | p. 25 |
Sequential Decisions | p. 26 |
Uncertain Events | p. 27 |
Consequences | p. 29 |
The Time Value of Money: A Special Kind of Trade-Off | p. 30 |
Larkin Oil | p. 33 |
Structuring Decisions | p. 43 |
Structuring Values | p. 44 |
Hiring a Summer Intern | p. 44 |
Fundamental and Means Objectives | p. 46 |
Getting the Decision Context Right | p. 51 |
Structuring Decisions: Influence Diagrams | p. 52 |
Influence Diagrams and the Fundamental-Objectives Hierarchy | p. 54 |
Using Arcs to Represent Relationships | p. 55 |
Some Basic Influence Diagrams | p. 57 |
Constructing an Influence Diagram (Optional) | p. 65 |
Toxic Chemicals and the Epa | p. 65 |
Structuring Decisions: Decision Trees | p. 69 |
Decision Trees and the Objectives Hierarchy | p. 71 |
Some Basic Decision Trees | p. 72 |
Decision Trees and Influence Diagrams Compared | p. 76 |
Decision Details: Defining Elements of the Decision | p. 76 |
More Decision Details: Cash Flows and Probabilities | p. 78 |
Defining Measurement Scales for Fundamental Objectives | p. 79 |
Using PrecisionTree for Structuring Decisions | p. 83 |
Making Choices | p. 111 |
Texaco Versus Pennzoil | p. 111 |
Decision Trees and Expected Monetary Value | p. 115 |
Solving Influence Diagrams: Overview | p. 119 |
Solving Influence Diagrams: The Details (Optional) | p. 121 |
Solving Influence Diagrams: An Algorithm (Optional) | p. 127 |
Risk Profiles | p. 128 |
Dominance: An Alternative to EMV | p. 133 |
Making Decisions with Multiple Objectives | p. 137 |
The Summer Job | p. 138 |
Analysis: One Objective at a Time | p. 140 |
Subjective Ratings for Constructed Attribute Scales | p. 140 |
Assessing Trade-Off Weights | p. 142 |
Analysis: Expected Values and Risk Profiles for Two Objectives | p. 143 |
Decision Analysis Using PrecisionTree | p. 146 |
Sensitivity Analysis | p. 174 |
Eagle Airlines | p. 174 |
Sensitivity Analysis: A Modeling Approach | p. 175 |
Problem Identification and Structure | p. 176 |
One-Way Sensitivity Analysis | p. 179 |
Tornado Diagrams | p. 180 |
Dominance Considerations | p. 181 |
Two-Way Sensitivity Analysis | p. 183 |
Sensitivity to Probabilities | p. 184 |
Two-Way Sensitivity Analysis for Three Alternatives (Optional) | p. 188 |
Investing in the Stock Market | p. 189 |
Sensitivity Analysis in Action | p. 192 |
Heart Disease in Infants | p. 192 |
Sensitivity Analysis Using TopRank and PrecisionTree | p. 193 |
Sensitivity Analysis: A Built-In Irony | p. 206 |
Creativity and Decision Making | p. 217 |
What Is Creativity? | p. 218 |
Theories of Creativity | p. 219 |
Chains of Thought | p. 219 |
Phases of the Creative Process | p. 220 |
Blocks to Creativity | p. 222 |
The Monk and the Mountain | p. 222 |
Making Cigars | p. 223 |
Ping-Pong Ball in a Pipe | p. 227 |
Value-Focused Thinking for Creating Alternatives | p. 230 |
Transportation of Nuclear Waste | p. 231 |
Other Creativity Techniques | p. 233 |
Creating Decision Opportunities | p. 239 |
Modeling Uncertainty | p. 247 |
Probability Basics | p. 249 |
A Little Probability Theory | p. 250 |
Venn Diagrams | p. 250 |
More Probability Formulas | p. 251 |
Uncertain Quantities | p. 256 |
Examples | p. 272 |
Oil Wildcatting | p. 272 |
John Hinckley's Trial | p. 278 |
Decision-Analysis Software and Bayes' Theorem | p. 280 |
Subjective Probability | p. 295 |
Uncertainty and Public Policy | p. 295 |
Probability: A Subjective Interpretation | p. 297 |
Accounting for Contingent Losses | p. 298 |
Assessing Discrete Probabilities | p. 299 |
Assessing Continuous Probabilities | p. 303 |
Pitfalls: Heuristics and Biases | p. 311 |
Tom W. | p. 311 |
Decomposition and Probability Assessment | p. 315 |
Experts and Probability Assessment: Pulling It All Together | p. 321 |
Climate Change at Yucca Mountain, Nevada | p. 324 |
Coherence and the Dutch Book (Optional) | p. 326 |
Constructing Distributions Using RISKview | p. 328 |
Theoretical Probability Models | p. 352 |
Theoretical Models Applied | p. 353 |
The Binomial Distribution | p. 354 |
The Poisson Distribution | p. 358 |
The Exponential Distribution | p. 361 |
The Normal Distribution | p. 363 |
The Beta Distribution | p. 369 |
Viewing Theoretical Distributions with RISKview | p. 373 |
Using Data | p. 398 |
Using Data to Construct Probability Distributions | p. 398 |
Halfway Houses | p. 400 |
Using Data to Fit Theoretical Probability Models | p. 404 |
Fitting Distributions to Data | p. 405 |
Using Data to Model Relationships | p. 412 |
The Regression Approach | p. 414 |
Natural Conjugate Distributions (Optional) | p. 436 |
A Bayesian Approach to Regression Analysis (Optional) | p. 445 |
Monte Carlo Simulation | p. 459 |
Fashions | p. 460 |
Using Uniform Random Numbers as Building Blocks | p. 463 |
General Uniform Distributions | p. 464 |
Exponential Distributions | p. 465 |
Discrete Distributions | p. 466 |
Other Distributions | p. 466 |
Simulating Spreadsheet Models Using @RISK | p. 466 |
Simulation, Decision Trees, and Influence Diagrams | p. 486 |
Value of Information | p. 496 |
Investing in the Stock Market | p. 496 |
Value of Information: Some Basic Ideas | p. 497 |
Expected Value of Perfect Information | p. 500 |
Expected Value of Imperfect Information | p. 502 |
Value of Information in Complex Problems | p. 508 |
Value of Information, Sensitivity Analysis, and Structuring | p. 509 |
Seeding Hurricanes | p. 510 |
Value of Information and Nonmonetary Objectives | p. 511 |
Value of Information and Experts | p. 512 |
Calculating EVPI and EVII with PrecisionTree | p. 512 |
Modeling Preferences | p. 525 |
Risk Attitudes | p. 527 |
E. H. Harriman Fights for the Northern Pacific Railroad | p. 528 |
Risk | p. 529 |
Risk Attitudes | p. 531 |
Investing in the Stock Market, Revisited | p. 533 |
Expected Utility, Certainty Equivalents, and Risk Premiums | p. 535 |
Keeping Terms Straight | p. 539 |
Utility Function Assessment | p. 539 |
Risk Tolerance and the Exponential Utility Function | p. 543 |
Modeling Preferences Using PrecisionTree | p. 546 |
Decreasing and Constant Risk Aversion (Optional) | p. 551 |
Some Caveats | p. 556 |
Utility Axioms, Paradoxes, and Implications | p. 571 |
Preparing for an Influenza Outbreak | p. 571 |
Axioms for Expected Utility | p. 572 |
Paradoxes | p. 578 |
Implications | p. 582 |
A Final Perspective | p. 586 |
Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function | p. 598 |
Objectives and Attributes | p. 600 |
Trading Off Conflicting Objectives: The Basics | p. 602 |
The Additive Utility Function | p. 604 |
Assessing Individual Utility Functions | p. 610 |
Assessing Weights | p. 614 |
Keeping Concepts Straight: Certainty versus Uncertainty | p. 620 |
An Example: Library Choices | p. 621 |
The Eugene Public Library | p. 621 |
Using Software for Multiple-Objective Decisions | p. 628 |
Conflicting Objectives II: Multiattribute Utility Models with Interactions | p. 644 |
Multiattribute Utility Functions: Direct Assessment | p. 645 |
Independence Conditions | p. 647 |
Determining Whether Independence Exists | p. 648 |
Using Independence | p. 650 |
Additive Independence | p. 651 |
Substitutes and Complements | p. 654 |
Assessing a Two-Attribute Utility Function | p. 654 |
The Blood Bank | p. 655 |
Three or More Attributes (Optional) | p. 659 |
When Independence Fails | p. 660 |
Multiattribute Utility in Action: BC Hydro | p. 661 |
Strategic Decisions at BC Hydro | p. 661 |
Conclusion and Further Reading | p. 675 |
A Decision-Analysis Reading List | p. 676 |
Appendixes | p. 679 |
Binomial Distribution: Individual Probabilities | p. 680 |
Binomial Distribution: Cumulative Probabilities | p. 688 |
Poisson Distribution: Individual Probabilities | p. 696 |
Poisson Distribution: Cumulative Probabilities | p. 701 |
Normal Distribution: Cumulative Probabilities | p. 706 |
Beta Distribution: Cumulative Probabilities | p. 710 |
Answers to Selected Exercises | p. 719 |
Credits | p. 721 |
Author Index | p. 722 |
Subject Index | p. 725 |
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