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Book Details
Abstract
For courses in Decision Making and Engineering.
The Fundamentals of Analyzing and Making Decisions
Foundations of Decision Analysis is a groundbreaking text that explores the art of decision making, both in life and in professional settings. By exploring themes such as dealing with uncertainty and understanding the distinction between a decision and its outcome, the First Edition teaches students to achieve clarity of action in any situation.
The book treats decision making as an evolutionary process from a scientific standpoint. Strategic decision-making analysis is presented as a tool to help students understand, discuss, and settle on important life choices. Through this text, students will understand the specific thought process that occurs behind approaching any decision to make easier and better life choices for themselves.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Cover\r | Cover | ||
| Title\r | TitlePage | ||
| Copyright\r | Copyright | ||
| Brief Contents | 3 | ||
| Contents\r | 5 | ||
| Chapter 1: Introduction to Quality Decision Making | 23 | ||
| 1.1 Introduction | 23 | ||
| 1.2 Normative Vs. Descriptive | 23 | ||
| 1.3 Declaring a Decision | 26 | ||
| 1.4 Thought Vs. Action | 29 | ||
| 1.5 What is a Decision? | 30 | ||
| 1.6 Decision Vs. Outcome | 32 | ||
| 1.7 Clarity of Action | 35 | ||
| 1.8 What is a Good Decision? | 36 | ||
| 1.9 Summary | 40 | ||
| Key Terms | 41 | ||
| Problems | 42 | ||
| Chapter 2: Experiencing a Decision | 44 | ||
| 2.1 Introduction | 44 | ||
| 2.2 Analysis of a Decision: The Thumbtack and the Medallion Example | 44 | ||
| 2.3 Lessons Learned from the Thumbtack and Medallion Example | 53 | ||
| 2.4 Summary | 57 | ||
| Key Terms | 57 | ||
| Appendix A: Results of the Thumbtack Demonstration | 58 | ||
| Problems | 59 | ||
| Chapter 3: Clarifying Values | 63 | ||
| 3.1 Introduction | 63 | ||
| 3.2 Value in Use and Value in Exchange | 63 | ||
| 3.3 Values Around a Cycle of Ownership | 67 | ||
| 3.4 Summary | 72 | ||
| Key Terms | 73 | ||
| Problems | 74 | ||
| Chapter 4: Precise Decision Language | 77 | ||
| 4.1 Introduction | 77 | ||
| 4.2 Lego-Like Precision | 77 | ||
| 4.3 Precise Decision Language | 78 | ||
| 4.4 Experts and Distinctions | 79 | ||
| 4.5 Mastery | 81 | ||
| 4.6 Creating Your Own Distinctions | 82 | ||
| 4.7 Footnote | 82 | ||
| 4.8 Summary | 82 | ||
| Key Terms | 82 | ||
| Problems | 83 | ||
| Chapter 5: Possibilities | 84 | ||
| 5.1 Overview | 84 | ||
| 5.2 Creating Distinctions | 84 | ||
| 5.3 The Possibility Tree | 87 | ||
| 5.4 Measures | 94 | ||
| 5.5 Sumary | 96 | ||
| Key Terms | 97 | ||
| Problems | 98 | ||
| Chapter 6: Handling Uncertainty | 100 | ||
| 6.1 Introduction | 100 | ||
| 6.2 Describing Degree of Belief by Probability | 100 | ||
| 6.3 The Probability Tree | 104 | ||
| 6.4 Several Degrees of Distinction | 113 | ||
| 6.5 Multiple Degrees of Distinction | 113 | ||
| 6.6 Probability Trees Using Multiple Distinctions | 116 | ||
| 6.7 Adding Measures to the Probability Tree | 123 | ||
| 6.8 Multiple Measures | 131 | ||
| 6.9 Summary | 133 | ||
| Key Terms | 134 | ||
| Appendix A: The Chain Rule for Distinctions: Calculating Elemental Probabilities | 135 | ||
| Appendix B: Let’s Make a Deal Commentary | 137 | ||
| Appendix C: Further Discussion Related to the Example: At Least One Boy | 140 | ||
| Problems | 141 | ||
| Chapter 7: Relevance | 145 | ||
| 7.1 Introduction | 145 | ||
| 7.2 Relevance with Simple Distinctions | 145 | ||
| 7.3 Is Relevance Mutual? | 146 | ||
| 7.4 Relevance Diagrams | 148 | ||
| 7.5 Alternate Asessment Orders | 152 | ||
| 7.6 Relevance Depends on Knowledge | 154 | ||
| 7.7 Distinctive Vs. Asociative Logic | 159 | ||
| 7.8 The Third Factor | 160 | ||
| 7.9 Multi-Degree Relevance | 163 | ||
| 7.10 Summary | 163 | ||
| Key Terms | 164 | ||
| Appendix A: More on Relevance Diagrams and Arrow Reversals | 165 | ||
| Problems | 168 | ||
| Chapter 8: Rules of Actional Thought | 178 | ||
| 8.1 Introduction | 178 | ||
| 8.2 Using Rules for Decision Making | 178 | ||
| 8.3 The Decision Situation | 180 | ||
| 8.4 The Five Rules of Actional Thought | 181 | ||
| 8.5 Summary | 187 | ||
| Key Terms | 188 | ||
| Problems | 189 | ||
| Chapter 9: The Party Problem | 198 | ||
| 9.1 Introduction | 198 | ||
| 9.2 The Party Problem | 198 | ||
| 9.3 Simplifying the Rules: E-Value | 204 | ||
| 9.4 Understanding the Value of the Party Problem | 209 | ||
| 9.5 Summary | 213 | ||
| Key Terms | 213 | ||
| Appendix A | 214 | ||
| Problems | 215 | ||
| Chapter 10: Using a Value Measure | 216 | ||
| 10.1 Introduction | 216 | ||
| 10.2 Money as a Value Measure | 216 | ||
| 10.3 u-curves | 219 | ||
| 10.4 Valuing Clairvoyance | 223 | ||
| 10.5 Jane’s Party Problem | 227 | ||
| 10.6 Attitudes toward Risk | 230 | ||
| 10.7 Mary’s Party Problem | 233 | ||
| 10.8 Summary | 235 | ||
| Key Terms | 235 | ||
| Problems | 236 | ||
| Chapter 11: Risk Attitude | 239 | ||
| 11.1 Introduction | 239 | ||
| 11.2 Wealth Risk Attitude | 239 | ||
| 11.3 Buying and Selling a Deal Around a Cycle of Ownership | 240 | ||
| 11.4 The Delta Property | 243 | ||
| 11.5 Risk Odds | 246 | ||
| 11.6 Delta Property Simplifications | 251 | ||
| 11.7 Other Forms of Exponential u-Curve | 253 | ||
| 11.8 Direct Assessment of Risk Tolerance | 254 | ||
| 11.9 Summary | 260 | ||
| Key Terms | 261 | ||
| Problems | 262 | ||
| Chapter 12: Sensitivity Analysis | 269 | ||
| 12.1 Introduction | 269 | ||
| 12.2 Kim’s Sensitivity to Probability of Sunshine | 269 | ||
| 12.3 Certain Equivalent Sensitivity | 271 | ||
| 12.4 Value of Clairvoyance Sensitivity to Probability of Sunshine | 272 | ||
| 12.5 Jane’s Sensitivity to Probability of Sunshine | 273 | ||
| 12.6 Comparison of Kim’s and Jane’s Value of Clairvoyance Sensitivities | 274 | ||
| 12.7 Risk Sensitivity Profile | 276 | ||
| 12.8 Summary | 278 | ||
| Key Terms | 278 | ||
| Problems | 279 | ||
| Chapter 13: Basic Information Gathering | 287 | ||
| 13.1 Introduction | 287 | ||
| 13.2 The Value of Information | 287 | ||
| 13.3 The Acme Rain Detector | 289 | ||
| 13.4 General Observations on Experiments | 295 | ||
| 13.5 Asymmetric Experiments | 299 | ||
| 13.6 Information Gathering Equivalents | 302 | ||
| 13.7 Summary | 305 | ||
| Problems | 307 | ||
| Chapter 14: Decision Diagrams | 314 | ||
| 14.1 Introduction | 314 | ||
| 14.2 Nodes in the Decision Diagram | 314 | ||
| 14.3 Arrows in Decision Diagrams | 315 | ||
| 14.4 Value of Clairvoyance | 317 | ||
| 14.5 Imperfect Information | 318 | ||
| 14.6 Decision Tree Order | 318 | ||
| 14.7 Detector Use Decision | 319 | ||
| 14.8 Summary | 322 | ||
| Key Terms | 322 | ||
| Problems | 323 | ||
| Chapter 15: Encoding a Probability Distribution on a Measure | 330 | ||
| 15.1 Introduction | 330 | ||
| 15.2 Probability Encoding | 332 | ||
| 15.3 Fractiles of a Probability Distribution | 338 | ||
| 15.4 Summary | 346 | ||
| Key Terms | 346 | ||
| Problems | 347 | ||
| Answers to Problem 2 | 348 | ||
| Chapter 16: From Phenomenon to Asesment | 349 | ||
| 16.1 Introduction | 349 | ||
| 16.2 Information Transmission | 349 | ||
| 16.3 Perception | 350 | ||
| 16.4 Cognition | 351 | ||
| 16.5 Motivation | 355 | ||
| 16.6 Summary | 355 | ||
| Key Terms | 355 | ||
| Chapter 17: Framing a Decision | 356 | ||
| 17.1 Introduction | 356 | ||
| 17.2 Making a Decision | 356 | ||
| 17.3 Selecting a Frame | 357 | ||
| 17.4 Summary | 368 | ||
| Key Terms | 368 | ||
| Problems | 369 | ||
| Chapter 18: Valuing Information from Multiple Sources\r | 370 | ||
| 18.1 Introduction | 370 | ||
| 18.2 The Beta Rain Detector | 370 | ||
| 18.3 Clarifying the Value of Joint Clairvoyance on Two Distinctions | 377 | ||
| 18.4 Value of Information for Multiple Uncertainties | 380 | ||
| 18.5 Approaching Clairvoyance with Multiple Acme Detectors | 385 | ||
| 18.6 Valuing Individually Immaterial Multiple Detectors | 394 | ||
| 18.7 Summary | 397 | ||
| Key Terms | 398 | ||
| Problems | 399 | ||
| Chapter 19: Options | 400 | ||
| 19.1 Introduction | 400 | ||
| 19.2 Contractual and Non-Contractual Options | 400 | ||
| 19.3 Option Price, Exercise Price, and Option Value | 401 | ||
| 19.4 Simple Option Analysis | 402 | ||
| 19.5 Consequences of Failure to Recognize Options | 405 | ||
| 19.6 Jane’s Party Revisited | 408 | ||
| 19.7 Value of Clairvoyance as an Option | 410 | ||
| 19.8 Sequential Information Options | 411 | ||
| 19.9 Sequential Detector Options | 414 | ||
| 19.10 Creating Options | 414 | ||
| 19.11 Summary | 419 | ||
| Key Terms | 419 | ||
| Problems | 420 | ||
| Chapter 20: Detectors with Multiple Indications | 421 | ||
| 20.1 Introduction | 421 | ||
| 20.2 Detector with 100 Indications | 422 | ||
| 20.3 The Continuous Beta Detector | 439 | ||
| 20.4 Summary | 445 | ||
| Key Terms | 445 | ||
| Problems | 446 | ||
| Chapter 21: Decisions with Influences | 447 | ||
| 21.1 Introduction | 447 | ||
| 21.2 Shirley’s Problem | 447 | ||
| 21.3 Summary | 462 | ||
| Key Terms | 462 | ||
| Problems | 463 | ||
| Chapter 22: The Logarithmic u-Curve | 464 | ||
| 22.1 Introduction | 464 | ||
| 22.2 The Logarithmic u-Curve | 465 | ||
| 22.3 Deals with Large Monetary Prospects for a DeltaPerson | 469 | ||
| 22.4 Properties of the Logarithmic u-Curve | 473 | ||
| 22.5 Certain Equivalent of Two Mutually Irrelevant Deal | 478 | ||
| 22.6 The St. Petersburg Paradox | 481 | ||
| 22.7 Summary | 484 | ||
| Key Terms | 485 | ||
| Appendix A: The Logarithmic Function and Its Properties | 486 | ||
| Appendix B: The Risk-Aversion Function | 487 | ||
| Appendix C: A Student’s Question Following an Economist Article | 488 | ||
| Problems | 493 | ||
| Chapter 23: The Linear Risk Tolerance u-Curve | 495 | ||
| 23.1 Introduction | 495 | ||
| 23.2 Linear Risk Tolerance | 495 | ||
| 23.3 Summary | 503 | ||
| Key Terms | 503 | ||
| Appendix A: Derivation of Linear Risk Tolerance u-Curve | 504 | ||
| Appendix B: Student’s Problem Using Linear Risk Tolerance u-Curve | 505 | ||
| Problems | 507 | ||
| Chapter 24: Aproximate Expresions for the Certain Equivalent | 508 | ||
| 24.1 Introduction | 508 | ||
| 24.2 Moments of a Measure | 508 | ||
| 24.3 Central Moments of a Measure | 512 | ||
| 24.4 Approximating the Certain Equivalent Using First and Second Central Moments | 513 | ||
| 24.5 Approximating the Certain Equivalent Using Higher Order Moments | 515 | ||
| 24.6 Cumulants | 518 | ||
| 24.7 Summary | 518 | ||
| Key Terms | 519 | ||
| Problems | 520 | ||
| Chapter 25: Deterministic and Probabilistic Dominance\r | 521 | ||
| 25.1 Introduction | 521 | ||
| 25.2 Deterministic Dominance | 521 | ||
| 25.3 First-Order Probabilistic Dominance | 526 | ||
| 25.4 Second-Order Probabilistic Dominance | 530 | ||
| 25.5 Dominance for Alternatives in the Party Problem | 534 | ||
| 25.6 Summary | 537 | ||
| Key Terms | 537 | ||
| Problems | 538 | ||
| Chapter 26: Decisions with Multiple Attributes (1)–Ordering Prospects with Preference and Value Functions | 539 | ||
| 26.1 Introduction | 539 | ||
| 26.2 Step 1: Direct Vs. Indirect Values | 540 | ||
| 26.3 Step 2: Ordering Prospects Characterized by Multiple “Direct Value” Attributes | 544 | ||
| 26.4 Summary | 551 | ||
| Key Terms | 552 | ||
| Appendix A: Deriving the Relation Between Increments in x and y as a Function of η in the Preference Function | 553 | ||
| Problems | 554 | ||
| Chapter 27: Decisions with Multiple Attributes (2)–Value Functions for Investment Cash Flows: Time Preference | 555 | ||
| 27.1 Introduction | 555 | ||
| 27.2 Rules for Evaluating Investment Cash Flows | 556 | ||
| 27.3 Methods Not Equivalent to the Present Equivalent | 567 | ||
| 27.4 Cash Flows: A Single Measure | 570 | ||
| 27.5 Summary | 570 | ||
| Key Terms | 570 | ||
| Problems | 571 | ||
| Chapter 28: Decisions With Multiple Attributes (3)–Preference Probabilities Over Value | 572 | ||
| 28.1 Introduction | 572 | ||
| 28.2 Stating Preference Probabilities with Two Attributes | 573 | ||
| 28.3 Stating Preference Probabilities with a Value Function | 574 | ||
| 28.4 Stating a u-Curve Over the Value Function | 574 | ||
| 28.5 The Value Certain Equivalent | 576 | ||
| 28.6 Other u-Function Approaches | 578 | ||
| 28.7 Stating a u-Curve Over an Individual Attribute within the Value Function | 579 | ||
| 28.8 Valuing Uncertain Cash Flows | 582 | ||
| 28.9 Discussion | 586 | ||
| 28.10 Summary | 587 | ||
| Key Terms | 587 | ||
| Problems | 588 | ||
| Chapter 29: Betting on Disparate Belief | 589 | ||
| 29.1 Introduction | 589 | ||
| 29.2 Betting on Disparate Probabilities | 589 | ||
| 29.3 Practical Use | 593 | ||
| 29.4 Summary | 594 | ||
| Key Terms | 594 | ||
| Problems | 595 | ||
| Chapter 30: Learning From Experimentation | 596 | ||
| 30.1 Introduction | 596 | ||
| 30.2 Assigning Probability of Head and Tail for the Thumbtack | 597 | ||
| 30.3 Probability of Heads on Next Two Tosses | 598 | ||
| 30.4 Probability of Any Number of Heads and Tails | 599 | ||
| 30.5 Learning from Observation | 600 | ||
| 30.6 Conjugate Distributions | 603 | ||
| 30.7 Does Observing a Head Make the Probability of a Head on the Next Toss More Likely? | 604 | ||
| 30.8 Another Thumbtack Demonstration | 605 | ||
| 30.9 Summary | 608 | ||
| Key Terms | 608 | ||
| Problems | 609 | ||
| Chapter 31: Auctions and Biding\r | 610 | ||
| 31.1 Introduction | 610 | ||
| 31.2 Another Thumbtack Demonstration | 610 | ||
| 31.3 Auctions 1 and 3 for a Deltaperson | 615 | ||
| 31.4 Non-Deltaperson Analysis | 621 | ||
| 31.5 The Value of the Bidding Opportunity for Auction 2 | 623 | ||
| 31.6 The Winner’s Curse | 627 | ||
| 31.7 Summary | 639 | ||
| Key Terms | 640 | ||
| Problems | 641 | ||
| Chapter 32: Evaluating, Scaling, and Sharing Uncertain Deals | 643 | ||
| 32.1 Introduction | 643 | ||
| 32.2 Scaling and Sharing Risk | 643 | ||
| 32.3 Scaling an Uncertain Deal | 644 | ||
| 32.4 Risk Sharing of Uncertain Deals | 647 | ||
| 32.5 Optimal Investment in a Portfolio | 649 | ||
| 32.6 Summary | 658 | ||
| Key Terms | 659 | ||
| Appendix A: Covariance and Correlation | 660 | ||
| Appendix B: Scalar (Dot) Product of Vectors | 665 | ||
| Appendix C: 2 × 2 and 3 × 3 Matrix Multiplications and Matrix Inversion | 666 | ||
| Problems | 669 | ||
| Chapter 33: Making Risky Decisions | 670 | ||
| 33.1 Introduction | 670 | ||
| 33.2 A Painful Dilemma | 670 | ||
| 33.3 Small Probabilities | 673 | ||
| 33.4 Using Micromort Values | 673 | ||
| 33.5 Applications | 675 | ||
| 33.6 Facing Larger Probabilities of Death | 677 | ||
| 33.7 Summary | 680 | ||
| Key Terms | 680 | ||
| Problems | 681 | ||
| Chapter 34: Decisions with a High Probability of Death\r | 683 | ||
| 34.1 Introduction | 683 | ||
| 34.2 Value Function for Remaining Life Years and Consumption | 683 | ||
| 34.3 Assigning a u-Curve Over the Value Function | 686 | ||
| 34.4 Determining Micromort Values | 689 | ||
| 34.5 Equivalent Perfect Life Probability (EPlP) | 695 | ||
| 34.6 Summary | 697 | ||
| Key Terms | 697 | ||
| Appendix A: Mortality Table for 30-Year-Old Male | 698 | ||
| Appendix B: Example of a Black Pill Calculation, x = 10,000 | 701 | ||
| Appendix C: Example of a White Pill Calculation, x = 10,000 | 704 | ||
| Problems | 707 | ||
| Chapter 35: Discretizing Continuous Probability Distributions\r | 708 | ||
| 35.1 Introduction | 708 | ||
| 35.2 Equal Areas Method | 709 | ||
| 35.3 Caution with Discretization | 713 | ||
| 35.4 Accuracy of 10–50–90 Approximate Method for Equal Areas | 715 | ||
| 35.5 Moments of Discrete and Continuous Measures | 718 | ||
| 35.6 Moment Matching Method | 718 | ||
| 35.7 Summary | 720 | ||
| Key Terms | 720 | ||
| Appendix A: Rationale for Equal Areas Method | 721 | ||
| Problems | 724 | ||
| Chapter 36: Solving Decision Problems by Simulation | 725 | ||
| 36.1 Introduction | 725 | ||
| 36.2 Using Simulation for Solving Problems | 725 | ||
| 36.3 Simulating Decisions Having a Single Discrete Distinction | 726 | ||
| 36.4 Decisions with Multiple Discrete Distinctions | 729 | ||
| 36.5 Simulating a Measure with a Continuous Distribution | 732 | ||
| 36.6 Simulating Mutually Irrelevant Distinctions | 736 | ||
| 36.7 Value of Information with Simulation | 738 | ||
| 36.8 Simulating Multiple Distinctions with Relevance | 742 | ||
| 36.9 Summary | 744 | ||
| Key Terms | 744 | ||
| Problems | 745 | ||
| Chapter 37: The Decision Analysis Cycle | 746 | ||
| 37.1 Introduction | 746 | ||
| 37.2 The Decision Analysis Cycle | 746 | ||
| 37.3 The Model Sequence | 756 | ||
| 37.4 Summary | 767 | ||
| Key Terms | 767 | ||
| Appendix A: Open Loop and Closed Loop Sensitivity for the Bidding Decision | 768 | ||
| Chapter 38: Topics in Organizational Decision Making\r | 775 | ||
| 38.1 Introduction | 775 | ||
| 38.2 Operating to Maximize Value | 776 | ||
| 38.3 Issues When Operating with Budgets | 778 | ||
| 38.4 Issues with Incentive Structures | 779 | ||
| 38.5 A Common Issue: Multiple Specifications Vs. Tradeoffs | 780 | ||
| 38.6 Need for a Corporate Risk Tolerance | 781 | ||
| 38.7 Common Motivational Biases in Organizations | 785 | ||
| 38.8 Summary | 787 | ||
| Key Terms | 787 | ||
| Problems | 788 | ||
| Chapter 39: Coordinating the Decision Making of Large Groups\r | 789 | ||
| 39.1 Introduction | 789 | ||
| 39.2 Issues Contributing to Poor Group Decision Making | 789 | ||
| 39.3 Classifying Decision Problems | 791 | ||
| 39.4 Structuring Decision Problems within Organizations | 794 | ||
| 39.5 Example: The Fifth Generation Corvette | 799 | ||
| 39.6 Summary | 802 | ||
| Key Terms | 802 | ||
| Chapter 40: Decisions and Ethics\r | 803 | ||
| 40.1 Introduction | 803 | ||
| 40.2 The Role of Ethics in Decision Making | 804 | ||
| 40.3 Ethical Distinctions | 805 | ||
| 40.4 Harming, Stealing, and Truth Telling | 808 | ||
| 40.5 Ethical Codes | 811 | ||
| 40.6 Ethical Situations | 812 | ||
| 40.7 Summary | 814 | ||
| Key Terms | 815 | ||
| Problems | 816 | ||
| Index | 817 | ||
| A | 817 | ||
| B | 818 | ||
| C | 818 | ||
| D | 819 | ||
| E | 820 | ||
| F | 821 | ||
| G | 821 | ||
| H | 822 | ||
| I | 822 | ||
| J | 822 | ||
| L | 822 | ||
| M | 823 | ||
| N | 823 | ||
| O | 823 | ||
| P | 824 | ||
| Q | 825 | ||
| R | 826 | ||
| S | 826 | ||
| T | 827 | ||
| U | 827 | ||
| V | 828 | ||
| W | 829 | ||
| Z | 829 |