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Foundations of Decision Analysis, by Ronald A. Howard, Ali E. Abbas
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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 readers 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, readers will understand the specific thought process that occurs behind approaching any decision to make easier and better life choices for themselves.
- Sales Rank: #184590 in Books
- Brand: Howard, Ronald A./ Abbas, Ali E.
- Published on: 2015-01-31
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.30" w x 7.30" l, .0 pounds
- Binding: Hardcover
- 832 pages
Most helpful customer reviews
15 of 15 people found the following review helpful.
The most authoritative Decision Analysis book
By Roberto Ley-Borras
The core decision analysis community had been waiting for this book for many years. Amazon ran out of stock the day that they mailed the book to those who pre-ordered it. These comments are for readers who are interested in decision analysis but may be not that familiar with the authors or the book background. The list of its forty chapters is included at the end of these comments.
Ronald Howard is a key founder of the discipline and his writing, teaching and application of decision analysis has shaped the discipline. In addition, he is a most clear, logical and even fun to read writer. Ali Abbas is a major decision analysis scholar and innovator, and the Director of CREATE at USC.
This book is the outgrowth of the course notes that Ronald Howard developed and used for teaching decision analysis at Stanford over more than forty year. It is great that "the manuscript" is now published in an extended and enriched version.
The forty chapters of the book cover a wide range of interrelated concepts and techniques. A subset of the chapters was designed to be understood by a general audience. The book includes many other chapters that go deep into the underpinnings of the discipline. The book is written as a textbook but it is also a reference book.
The book uses simple examples carefully designed to learn a lot from them and logically builds a network of useful concepts from the "five rules of actional thought" (Howard's axiomatic basis for the discipline.) It includes a few exercises at the end of each chapter but it does not include a bibliography.
Amazon does not include (at this time) the list of chapters or the recommendations by the authors for different types of readers, but you can see them at the Pearson's sites that will be distributing the paperback Global Edition. For example at http://www.pearson.com.au/products/A-C-Abbas-Ali-Howard-Ronald/Foundations-of-Decision-Analysis-Global-Edition/9781292079691?R=9781292079691#
Amazon is currently offering only the hardcover edition by Pearson (even if Amazon says it is by Prentice-Hall).
This is a great book for any serious student of decision analysis and also for those who want to learn it rigorously for the first time.
Roberto Ley-Borrás
For quick reference I am including the list of chapters and recommendations.
Part 1 Defining a Good Decision
Chapter 1: Introduction to Quality Decision Making
Chapter 2: Experiencing a Decision
Part 2 Clear Thinking and Characterization
Chapter 3: Clarifying Values
Chapter 4: Precise Decision Language
Chapter 5: Possibilities
Chapter 6: Handling Uncertainty
Chapter 7: Relevance
Part 3 Making any Decision
Chapter 8: Rules of Actional Thought
Chapter 9: The Party Problem
Chapter 10: Using a Value Measure
Part 4 Building on the Rules
Chapter 11: Risk Attitude
Chapter 12: Sensitivity Analysis
Chapter 13: Basic Information Gathering
Chapter 14: Decision Diagrams
Part 5 Characterizing What you Know
Chapter 15: Encoding a Probability Distribution on a Measure
Chapter 16: From Phenomenon to Assessment
Part 6 Framing a Decision
Chapter 17: Framing a Decision
Part 7 Advanced Information Gathering
Chapter 18: Valuing Information from Multiple Sources
Chapter 19: Options
Chapter 20: Detectors with Multiple Indications
Chapter 21: Decisions with Influences
Part 8 Characterizing What You Want
Chapter 22: The Logarithmic u-Curve
Chapter 23: The Linear Risk Tolerance u-Curve
Chapter 24: Approximate Expressions for the Certain
Chapter 25: Deterministic and Probabilistic Dominance
Chapter 26: Decisions with Multiple Attributes (1)–Ordering Prospects with Preference and Value Functions
Chapter 27: Decisions with Multiple Attributes (2)–Value Functions for Investment Cash Flows: Time Preference
Chapter 28: Decisions with Multiple Attributes (3)–Preference Equivalent Probabilities Over Value
Part 9 Some Practical Extensions
Chapter 29: Betting on Disparate Belief
Chapter 30: Learning from Experimentation
Chapter 31: Auctions and Bidding
Chapter 32: Evaluating, Scaling, and Sharing Uncertain Deals
Chapter 33: Making Risky Decisions
Chapter 34: Decisions with a High Probability of Death
Part 10 Computing Decision Problems
Chapter 35: Discretizing Continuous Probability Distributions
Chapter 36: Solving Decision Problems by Simulation
Part 11 Professional Decisions
Chapter 37: The Decision Analysis Cycle
Chapter 38: Topics in Organizational Decision Making
Chapter 39: Coordinating the Decision Making of Large Groups
Part 12 Ethical Considerations
Chapter 40: Decisions and Ethics
Features & benefits
Foundations of Decision Analysis contains the following features to facilitate learning:
An easy to read text accessible by all audiences
• The book approaches the process of decision making from a mathematical standpoint, but many of its chapters steer clear of complex equations so basic fundamentals can be easily understood by a general audience.
o Chapters 1-17 introduce foundations of decision analysis without mathematical or computational emphasis. Topics include characterizing a decision, the rules of actional thought, u-curves, sensitivity analysis, probability encoding, and framing.
o Chapter 26 discusses multi-attribute decision problems with no uncertainty to prepare readers to approach these issues in real life when uncertainty is present.
o Chapter 29 teachers readers to make decisions based on differing beliefs using rules of probability.
o Chapter 33 explores decisions that involve a small probability of death.
o Chapters and 37-39 applies the decision analysis approach to large group settings.
o Chapter 40 discusses ethical consideration in decision making.
• Readers with more mathematical and computational preparation can benefit from the latter half of the book after understanding basic fundamentals presented in chapters 1-17.
o Chapters 18-25 discuss advanced information gathering from multiple sources, the concept of creating operations in our daily lives, u-curves that describe risk aversion, using approximate formulas for valuing deals, and the concept of probabilistic dominance relations to facilitate the best alternative.
o Chapters 27 and 28 uses a value function for cash flows to determine and explain multi-attribute problems with uncertainty.
o Chapter 30 teaches students to update probability after observing the results of an experiment.
o Chapter 31 explores using the basic concepts for decision analysis to determine the best bid at the value of bidding opportunity at a variety of auction types.
o Chapter 32 presents the concepts of risk scaling and sharing, exploring how decision makers can determine the best portion of an investment, how a partnership can share an investment, and how to establish the risk tolerance of a partnership.
o Chapter 34 analyzes situations in which the decision maker is exposed to a high probability of death.
o Chapters 35 and 36 teach students to solve decision making problems mathematically by using simulation and discretization.
o Numerical problems are exposed in tabular format to help facilitate completion.
The “Decision Analysis Core Concepts Map” is a pedagogical feature that helps students understand major concepts
• Provides a summary of major concepts that students can use as a reference of major points to grasp in each chapter.
• Concepts are presented in chronological order to make for an easy flow of understanding key information.
• Arrows are used between related concepts to show students what they must understand before approaching the next topic.
A text that teaches by real world example
• Chapter 37 presents a case study that exemplifies the decision making tools presented throughout the book in a real life setting.
11 of 11 people found the following review helpful.
Ron and Ali have done a masterful job of creating ...
By Carl S. Spetzler
Ron and Ali have done a masterful job of creating the textbook that accompanies the course that has changed many people. Again and again, I hear from the students that have taken the course: "This course has changed my life. I will never look at decisions that same way again." Thanks.
5 of 5 people found the following review helpful.
It is finally here. Thank you, Ron. ...
By Stephen Barrager
It is finally here. Thank you, Ron. Thank you, Ali. This is truly an important book. It captures not only the technical foundations of decision analysis, it captures Professor Howard's expertise in teaching the material. He knows how to make ideas simple and clear. I predict the book will become a classic. I hope students world wide will be able to afford it.
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