Making Hard Decisions With Decision Tools Suite Update 2004

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ISBN: 9780534421991 | 0534421997
Cover: Paperback
Copyright: 11/24/2003

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Author Biography

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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
Table of Contents provided by Ingram. All Rights Reserved.

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Making Hard Decisions With Decision Tools Suite Update 2004

Author Biography

Table of Contents

Supplemental Materials