The Science of Decision Making: A Problem-Based Approach Using Excel / Edition 1

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Overview

Provides the reader with a perspective on the efficient operation of complicated systems.
* Spreadsheets are used to employ and teach techniques.
* Includes the facets of probability that relate to decision making.
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Editorial Reviews

Booknews
This text/CD-ROM package introduces the science of decision making using a combination of problem-based learning, spreadsheet computation, and decision science. It emphasizes the links between operations research and economic reasoning, with inclusion of probability, but excludes nearly all of the algorithms that are a part of operations research, leaving them for more advanced courses. Examples are taken from engineering, economics, finance, operations management, business, and medical decision making. The text is useful for one-semester courses introducing deterministic models of decision making and stochastic methods. The CD-ROM contains Premium Solver for Education, TreePlan, and RiskSim, functions, and data sets. The author is on the faculty at Yale University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780471318279
  • Publisher: Wiley
  • Publication date: 8/28/2001
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 720
  • Product dimensions: 8.25 (w) x 11.00 (h) x 1.47 (d)

Meet the Author

Educated at Princeton and Northwestern Universities, Eric V. Denardo worked for AT&T and The Rand Corporation before joining the faculty of Yale University. His work is noted for its breadth, innovation, and elegance.
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Table of Contents

Preface.

PART A: INTRODUCTION.

The Science of Decision Making.

Getting Started with Spreadsheets.

PART B: USING LINEAR PROGRAMS.

Analyzing Solutions of Linear Programs.

A Survey of Linear Programs.

Networks.

Integer Programs.

PART C: PROBABILITY FOR DECISION MAKING.

Introduction to Probability Models.

Discrete Random Variables.

Decision Trees and Generalizations.

Utility Theory and Decision Analysis.

Continuous Random Variables.

PART D: STOCHASTIC SYSTEMS.

Inventory.

Markov Chains.

Queueing.

Simulation.

PART E: GAME THEORY.

Game Theory.

PART F: SOLVING LINEAR PROGRAMS.

Solving Linear Equations.

The Simplex Method.

Duality.

Appendix: Note on Excel.

Index.

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