| 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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