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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 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.

Foundations of Decision Analysis, Global Edition

• Part 1 Defining a Good Decision
• Chapter 1: Introduction to Quality Decision Making
• Chapter 2: Experiencing a Decision
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• 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
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• Part 3 Making any Decision
• Chapter 8: Rules of Actional Thought
• Chapter 9: The Party Problem
• Chapter 10: Using a Value Measure
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• Part 4 Building on the Rules
• Chapter 11: Risk Attitude
• Chapter 12: Sensitivity Analysis
• Chapter 13: Basic Information Gathering
• Chapter 14: Decision Diagrams
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• Part 5 Characterizing What you Know
• Chapter 15: Encoding a Probability Distribution on a Measure
• Chapter 16: From Phenomenon to Assessment
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• Part 6 Framing a Decision
• Chapter 17: Framing a Decision
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• 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
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• 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
• Chapter 27: Decisions with Multiple Attributes (2)–Value Functions
• Chapter 28: Decisions with Multiple Attributes (3)–Preference Equivalent
• Prospects with Preference and Value Functions
• for Investment Cash Flows: Time Preference
• Probabilities Over Value
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• 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
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• Part 10 Computing Decision Problems
• Chapter 35: Discretizing Continuous Probability Distributions
• Chapter 36: Solving Decision Problems by Simulation
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• 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
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• Part 12 Ethical Considerations
• Chapter 40: Decisions and Ethics Groups