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| Preface | |
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| Introduction to Decision Analysis | |
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| Gypsy Moths and the Oda | |
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| Why Are Decisions Hard? | |
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| Why Study Decision Analysis? | |
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| Subjective Judgments and Decision Making | |
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| The Decision-Analysis Process | |
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| Requisite Decision Models | |
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| Where Is Decision Analysis Used? | |
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| Where Does the Software Fit In? | |
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| Where Are We Going from Here? | |
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| Modeling Decisions | |
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| Elements of Decision Problems | |
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| Values and Objectives | |
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| Making Money: A Special Objective | |
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| Values and the Current Decision Context | |
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| Boeing's Supercomputer | |
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| Decisions to Make | |
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| Sequential Decisions | |
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| Uncertain Events | |
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| Consequences | |
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| The Time Value of Money: A Special Kind of Trade-Off | |
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| Larkin Oil | |
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| Structuring Decisions | |
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| Structuring Values | |
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| Hiring a Summer Intern | |
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| Fundamental and Means Objectives | |
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| Getting the Decision Context Right | |
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| Structuring Decisions: Influence Diagrams | |
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| Influence Diagrams and the Fundamental-Objectives Hierarchy | |
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| Using Arcs to Represent Relationships | |
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| Some Basic Influence Diagrams | |
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| The Basic Risky Decision | |
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| Imperfect Information | |
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| Sequential Decisions | |
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| Intermediate Calculations | |
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| Constructing an Influence Diagram (Optional) | |
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| Toxic Chemicals and the Epa | |
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| Some Common Mistakes | |
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| Multiple Representations and Requisite Models | |
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| Structuring Decisions: Decision Trees | |
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| Decision Trees and the Objectives Hierarchy | |
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| Some Basic Decision Trees | |
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| The Basic Risky Decision | |
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| Imperfect Information | |
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| Sequential Decisions | |
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| Decision Trees and Influence Diagrams Compared | |
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| Decision Details: Defining Elements of the Decision | |
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| More Decision Details: Cash Flows and Probabilities | |
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| Defining Measurement Scales for Fundamental Objectives | |
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| Using Precision Tree for Structuring Decisions | |
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| Constructing a Decision Tree for the Research-and-Development Decision | |
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| Constructing an Influence Diagram for the Basic Risky Decision | |
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| Making Choices | |
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| Texaco Versus Pennzoil | |
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| Decision Trees and Expected Monetary Value | |
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| Solving Influence Diagrams: Overview | |
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| Solving Influence Diagrams: The Details (Optional) | |
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| Solving Influence Diagrams: An Algorithm (Optional) | |
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| Risk Profiles | |
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| Cumulative Risk Profiles | |
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| Dominance: An Alternative to EMV | |
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| Making Decisions with Multiple Objectives | |
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| The Summer Job | |
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| Analysis: One Objective at a Time | |
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| Subjective Ratings for Constructed Attribute Scales | |
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| Assessing Trade-Off Weights | |
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| Analysis: Expected Values and Risk Profiles for Two Objectives | |
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| Decision Analysis Using PrecisionTree | |
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| Decision Trees | |
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| Influence Diagrams | |
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| Multiple-Attribute Models | |
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| Sensitivity Analysis | |
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| Eagle Airlines | |
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| Sensitivity Analysis: A Modeling Approach | |
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| Problem Identification and Structure | |
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| One-Way Sensitivity Analysis | |
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| Tornado Diagrams | |
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| Dominance Considerations | |
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| Two-Way Sensitivity Analysis | |
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| Sensitivity to Probabilities | |
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| Two-Way Sensitivity Analysis for Three Alternatives (Optional) | |
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| Investing in the Stock Market | |
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| Sensitivity Analysis in Action | |
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| Heart Disease in Infants | |
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| Sensitivity Analysis Using TopRank and PrecisionTree | |
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| Top Rank | |
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| PrecisionTree | |
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| Sensitivity Analysis: A Built-In Irony | |
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| Creativity and Decision Making | |
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| What Is Creativity? | |
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| Theories of Creativity | |
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| Chains of Thought | |
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| Phases of the Creative Process | |
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| Blocks to Creativity | |
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| Framing and Perceptual Blocks | |
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| The Monk and the Mountain | |
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| Making Cigars | |
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| Value-Based Blocks | |
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| Cultural and Environmental Blocks | |
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| Ping-Pong Ball in a Pipe | |
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| Organizational Issues | |
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| Value-Focused Thinking for Creating Alternatives | |
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| Fundamental Objectives | |
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| Means Objectives | |
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| Transportation of Nuclear Waste | |
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| The Decision Context | |
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| Other Creativity Techniques | |
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| Fluent and Flexible Thinking | |
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| Idea Checklists | |
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| Brainstorming | |
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| Metaphorical Thinking | |
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| Other Techniques | |
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| Creating Decision Opportunities | |
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| Modeling Uncertainty | |
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| Probability Basics | |
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| A Little Probability Theory | |
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| Venn Diagrams | |
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| More Probability Formulas | |
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| Uncertain Quantities | |
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| Discrete Probability Distributions | |
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| Expected Value | |
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| Variance and Standard Deviation | |
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| Covariance and Correlation for Measuring Dependence (Optional) | |
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| Continuous Probability Distributions | |
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| Stochastic Dominance Revisited | |
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| Stochastic Dominance and Multiple Attributes (Optional) | |
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| Probability Density Functions | |
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| Expected Value, Variance, and Standard Deviation: The Continuous Case | |
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| Covariance and Correlation: The Continuous Case (Optional) | |
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| Oil Wildcatting | |
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| John Hinckley's Trial | |
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| Decision-Analysis Software and Bayes' Theorem | |
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| Subjective Probability | |
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| Uncertainty and Public Policy | |
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| Probability: A Subjective Interpretation | |
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| Accounting for Contingent Losses | |
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| Assessing Discrete Probabilities | |
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| Assessing Continuous Probabilities | |
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| Pitfalls: Heuristics and Biases | |
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| Tom W. | |
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| Representativeness | |
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| Availability | |
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| Anchoring and Adjusting | |
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| Motivational Bias | |
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| Heuristics and Biases: Implications | |
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| Decomposition and Probability Assessment | |
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| Experts and Probability Assessment: Pulling It All Together | |
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| Climate Change at Yucca Mountain, Nevada | |
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| Coherence and the Dutch Book (Optional) | |
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| Constructing Distributions Using RISK view | |
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| Theoretical Probability Models | |
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| Theoretical Models Applied | |
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| The Binomial Distribution | |
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| The Poisson Distribution | |
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| The Exponential Distribution | |
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| The Normal Distribution | |
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| The Beta Distribution | |
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| Viewing Theoretical Distributions with RISK view | |
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| Discrete Distributions | |
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| Continuous Distributions | |
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| Using Data | |
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| Using Data to Construct Probability Distributions | |
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| Histograms | |
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| Empirical CDFs | |
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| Halfway Houses | |
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| Using Data to Fit Theoretical Probability Models | |
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| Fitting Distributions to Data | |
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| Using Data to Model Relationships | |
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| The Regression Approach | |
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| Estimation: The Basics | |
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| Estimation: More than One Conditioning Variable | |
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| Regression Analysis and Modeling: Some Do's and Don't's | |
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| Regression Analysis: Some Bells and Whistles | |
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| Regression Modeling: Decision Analysis versus Statistical Inference | |
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| An Admonition: Use with Care | |
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| Natural Conjugate Distributions (Optional) | |
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| Uncertainty About Parameters and Bayesian Updating | |
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| Binomial Distributions: Natural Conjugate Priors for p | |
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| Normal Distributions: Natural Conjugate Priors for [mu] | |
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| Predictive Distributions | |
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| Predictive Distributions: The Normal Case | |
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| Predictive Distributions: The Binomial Case | |
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| A Bayesian Approach to Regression Analysis (Optional) | |
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| Monte Carlo Simulation | |
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| Fashions | |
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| Using Uniform Random Numbers as Building Blocks | |
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| General Uniform Distributions | |
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| Exponential Distributions | |
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| Discrete Distributions | |
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| Other Distributions | |
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| Simulating Spreadsheet Models Using @RISK | |
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| Multiple Output Models | |
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| Distributions on Parameters (Optional) | |
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| Dependent Input Variables (Optional) | |
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| Simulation, Decision Trees, and Influence Diagrams | |
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| Value of Information | |
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| Investing in the Stock Market | |
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| Value of Information: Some Basic Ideas | |
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| Probability and Perfect Information | |
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| The Expected Value of Information | |
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| Expected Value of Perfect Information | |
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| Expected Value of Imperfect Information | |
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| Value of Information in Complex Problems | |
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| Value of Information, Sensitivity Analysis, and Structuring | |
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| Seeding Hurricanes | |
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| Value of Information and Nonmonetary Objectives | |
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| Value of Information and Experts | |
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| Calculating EVPI and EVII with PrecisionTree | |
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| EVPI | |
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| EVII | |
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| Modeling Preferences | |
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| Risk Attitudes | |
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| E. H. Harriman Fights for the Northern Pacific Railroad | |
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| Risk | |
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| Risk Attitudes | |
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| Investing in the Stock Market, Revisited | |
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| Expected Utility, Certainty Equivalents, and Risk Premiums | |
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| Keeping Terms Straight | |
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| Utility Function Assessment | |
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| Assessment Using Certainty Equivalents | |
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| Assessment Using Probabilities | |
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| Gambles, Lotteries, and Investments | |
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| Risk Tolerance and the Exponential Utility Function | |
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| Modeling Preferences Using PrecisionTree | |
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| Sensitivity Analysis of Risk Tolerance | |
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| Decreasing and Constant Risk Aversion (Optional) | |
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| Decreasing Risk Aversion | |
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| An Investment Example | |
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| Constant Risk Aversion | |
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| Some Caveats | |
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| Utility Axioms, Paradoxes, and Implications | |
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| Preparing for an Influenza Outbreak | |
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| Axioms for Expected Utility | |
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| Paradoxes | |
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| Implications | |
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| Implications for Utility Assessment | |
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| Managerial and Policy Implications | |
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| A Final Perspective | |
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| Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function | |
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| Objectives and Attributes | |
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| Trading Off Conflicting Objectives: The Basics | |
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| Choosing an Automobile: An Example | |
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| The Additive Utility Function | |
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| Choosing an Automobile: Proportional Scores | |
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| Assessing Weights: Pricing Out the Objectives | |
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| Indifference Curves | |
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| Assessing Individual Utility Functions | |
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| Proportional Scores | |
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| Ratios | |
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| Standard Utility-Function Assessment | |
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| Assessing Weights | |
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| Pricing Out | |
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| Swing Weighting | |
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| Lottery Weights | |
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| Keeping Concepts Straight: Certainty versus Uncertainty | |
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| An Example: Library Choices | |
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| The Eugene Public Library | |
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| Using Software for Multiple-Objective Decisions | |
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| Conflicting Objectives II: Multiattribute Utility Models with Interactions | |
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| Multiattribute Utility Functions: Direct Assessment | |
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| Independence Conditions | |
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| Preferential Independence | |
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| Utility Independence | |
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| Determining Whether Independence Exists | |
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| Using Independence | |
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| Additive Independence | |
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| Substitutes and Complements | |
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| Assessing a Two-Attribute Utility Function | |
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| The Blood Bank | |
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| Three or More Attributes (Optional) | |
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| When Independence Fails | |
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| Multiattribute Utility in Action: BC Hydro | |
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| Strategic Decisions at BC Hydro | |
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| Conclusion and Further Reading | |
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| A Decision-Analysis Reading List | |
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| Appendixes | |
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| Binomial Distribution: Individual Probabilities | |
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| Binomial Distribution: Cumulative Probabilities | |
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| Poisson Distribution: Individual Probabilities | |
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| Poisson Distribution: Cumulative Probabilities | |
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| Normal Distribution: Cumulative Probabilities | |
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| Beta Distribution: Cumulative Probabilities | |
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| Answers to Selected Exercises | |
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| Credits | |
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| Author Index | |
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| Subject Index | |