Description

Book Synopsis


Table of Contents
  • 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
  • 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
  • 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
  • Part 12 Ethical Considerations
  • Chapter 40: Decisions and Ethics Groups

Foundations of Decision Analysis Global Edition

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    Order before 4pm tomorrow for delivery by Fri 12 Jun 2026.

    A Paperback by Ali E. Abbas, Ronald Howard

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      View other formats and editions of Foundations of Decision Analysis Global Edition by Ali E. Abbas

      Publisher: Pearson Education
      Publication Date: 3/19/2015 12:00:00 AM
      ISBN13: 9781292079691, 978-1292079691
      ISBN10: 129207969X

      Description

      Book Synopsis


      Table of Contents
      • 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
      • 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
      • 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
      • Part 12 Ethical Considerations
      • Chapter 40: Decisions and Ethics Groups

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