Making Hard Decisions with Decision Tools Suite

Name: Making Hard Decisions with Decision Tools Suite
Price: 4.19 USD
Availability: InStock
ISBN: 9780495015086

ISBN-10: 0495015083

ISBN-13: 9780495015086

Edition: 2001 (Revised)

Authors: Robert T. Clemen, Terence Reilly

List price: $303.95

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MAKING HARD DECISIONS WITH DECISIONTOOLS is a special version of Bob Clemen's best-selling text, MAKING HARD DECISIONS. This straight-forward book teaches the fundamental ideas of decision analysis, without an overly technical explanation of the mathematics used in management science. This new version incorporates and implements the powerful DecisionTools by Palisade Corporation, the world's leading toolkit for risk and decision analysis. At the end of each chapter, topics are illustrated with step-by-step instructions for DecisionTools. This new version makes the text more useful and relevant to students to business and engineering.

Book details

List price: $303.95
Copyright year: 2001
Publisher: Brooks/Cole
Publication date: 12/8/2004
Binding: Hardcover
Pages: 752
Size: 7.75" wide x 9.75" long x 2.25" tall
Weight: 3.344
Language: English

Robert T. Clemen is Professor at the Fuqua School of Business at Duke University. He has been an active contributor to the field of decision analysis since earning his Ph.D. at Indiana University in 1984 and is an authority in the use of expert information in decision and risk analysis. He has interests in applying decision analysis in the areas of energy use and corporate sustainabiligy. Aside from his research interests, Bob has a strong focus on making decision analysis understandable to all students at all levels, ranging from high school students to executives.

Terence Reilly is an associate Professor of Mathematics at Babson College. His interests include developing innovative curriculum for MBA programs, particularly distance programs, along with simulation and decision analysis. His research interests are in developing sensitivity analysis techniques and fitting distribution curves to univariate and multivariate uncertainties. Recently, he has developed courses in financial methods using simulation and decision analysis.



Preface



Introduction To Decision Analysis


Why Are Decisions Hard?


Why Study Decision Analysis?


Subjective Judgements And Decision Making


The Decision Analysis Process


Where Is Decision Analysis Used


Where Does The Software Fit In?


Where Are We Going From Here?


Summary


Questions And Problems


Case Studies


References


Epilogue



Modeling Decisions



Elements Of Decision Problems


Values And Objectives


Making Money: A Special Objective


Values And The Current Decision Context


Decisions To Make


Sequential Decisions


Uncertain Events


Consequences


The Time Value Of Money: A Special Kind Of Trade-Off


Summary


Questions And Problems


Case Studies


References


Epilogue



Structuring Decisions


Structuring Values


Fundamental And Means Objectives


Getting The Decision Complex Right


Structuring Designs: Influence Diagrams


Influence Diagrams And The Fundamental-Objectives Hierarchy


Using Arcs To Represent Relationships


Some Basic Influence Diagrams


Constructing An Influence Diagram (Optional)


Structuring Decisions: Decision Trees


Decision Trees And Influence Diagrams Compared


Decision Details: Defining Details: Defining Elements Of The Decision


More Decision Details: Cash Flows And Probabilities


Using Precisiontree For Structuring Decisions


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Making Choices


Decision Trees And Expected Monetary Value


Solving Influence Diagrams: Overview


Solving Influence Diagrams: The Details (Optional)


Solving Influence Diagrams: An Algorithm (Optional)


Risk Profiles


Dominance: An Alternative To Emv


Making Decisions With Multiple Objectives


Analysis: One Objective At A Time


Subjective Ratings For Constructed Attribute Scales


Assessing Trade-Off Weights


Analysis: Expected Values And Risk Profiles For Two Objectives


Decision Analysis Using Precisontree


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Sensitivity Analysis


Sensitivity Analysis: A Modeling Approach


Problem Identification And Structure


One-Way Sensitivity Analysis


Tornado Diagrams


Dominance Considerations


Two-Way Sensitivity Analysis


Sensitivity To Probabilities


Two-Way Sensitivity Analysis For Three Alternatives (Optional)


Sensitivity Analysis In Action


Sensitivity Analysis Using Toprank And Precisiontree


Sensitivity Analysis: A Built-In Irony


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Creativity And Decision Making


What Is Creativity? Theories Of Creativity


Chains Of Thought


Phases Of The Creative Process


Blocks To Creativity


Cultural And Environmental Blocks


Value-Focused Thinking For Creating Alternatives


Other Creativity Techniques


Creating Decision Opportunities


Summary


Questions And Problems


Case Studies


References


Epilogue



Modeling Uncertainty



Probability Basics


A Little Probability Theory


Venn Diagrams


More Probability Formulas


Uncertain Quantities


Examples


Decision-Analysis Software And Bayes'' Theorem


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Subjective Probability


Probability: A Subjective Interpretation


Assessing Discrete Probabilities


Assessing Continuous Probabilities


Pitfalls: Heuristics And Biases


Decomposition And Probability Assessment


Experts And Probability Assessment: Pulling It All Together


Coherence And The Dutch Book (Optional)


Constructing Distributions Using Riskview


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Theoretical Probability Models


The Binomial Distribution


The Poisson Distribution


The Exponential Distribution


The Normal Distribution


The Beta Distribution


Viewing Theoretical Distributions With Riskview


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Using Data


Using Data To Construct Probability Distributions


Using Data To Fit Theoretical Probability Models


Fitting Distributions To Data


Using Data To Model Relationships


The Regression Approach


Natural Conjugate Distributions (Optional)


A Bayesian Approach To Regression Analysis (Optional)


Summary


Exercises


Questions And Problems


Case Studies


References



Monte Carlo Simulation


Using Uniform Random Numbers As Building Blocks


General Uniform Distributions


Exponential Distributions


Discrete Distributions


Other Distributions


Simulating Spreadsheet Models Using @Risk


Simulation, Decision Trees, And Influence Diagrams


Summary


Exercises


Questions And Problems


Case Studies


References



Value Of Information


Value Of Information: Some Basic Ideas


Expected Value Of Perfect Information


Expected Value Of Imperfect Information


Value Of Information In Complex Problems


Value Of Information, Sensitivity Analysis, And Structuring


Value Of Information And Nonmonetary Objectives


Value Of Information And Experts


Calculating Evpi And Evii With Precisiontree


Summary


Exercises


Questions And Problems


Case Studies


References



Modeling Preferences



Risk Attitudes


Risk


Risk Attitudes


Investing In The Stock Market, Revisited


Expected Utility, Certainty Equivalents, And Risk Premiums


Keeping Terms Straight


Utility Function Assessment


Risk Tolerance And The Exponential Utility Function


Modeling Preferences Using Precisiontree


Decreasing And Constant Risk Aversion (Optional)


Some Caveats


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Utility Axioms, Paradoxes, And Implications


Axioms For Expected Utility


Paradoxes


Implications


A Final Perspective


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Conflicting Objectives I: Fundamental Objectives And The Additive Utility Function Objectives And Attributes


Trading Off Conflicting Objectives: The Basics


The Additive Utility Function


Assessing Individual Utility Functions


Assessing Weights


Keeping Concepts Straight: Certainty Versus Uncertainty


An Example: Library Choices


Using Software For Multiple-Objective Decisions


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Conflicting Objectives II: Multiattribute Utility Models With Interactions


Multiattribute Utility Functions: Direct Assessment


Independence Conditions


Determining Whether Independence Exists


Using Independence


Additive Independence


Substitutes And Complements


Assessing A Two-Attribute Utility Function


Three Or More Attributes (Optional)


When Independence Fails


Multiattribute Utility In Action: Bc Hydro


Summary


Exercises


Questions And Problems


Case Studies


References


Epilogue



Conclusion And Further Reading


A Decision-Analysis Reading List



Binomial Distribution: Individual Probabilities



Binomial Distribution: Cumulative Probabilities



Poisson Distribution: Individual Probabilities



Poisson Distribution: Cumulative Probabilities



Normal Distribution: Cumulative Probabilities



Beta Distribution: Cumulative Probabilities


Answers To Selected Exercises


Author Index