Making Better Decisions: Decision Theory in Practice / Edition 1

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Overview

Making Better Decisions introduces readers to some of the principal aspects of decision theory, and examines how these might lead us to make better decisions.
  • Introduces readers to key aspects of decision theory and examines how they might help us make better decisions
  • Presentation of material encourages readers to imagine a situation and make a decision or a judgment
  • Offers a broad coverage of the subject including major insights from several sub-disciplines: microeconomic theory, decision theory, game theory, social choice, statistics, psychology, and philosophy
  • Explains these insights informally in a language that has minimal mathematical notation or jargon, even when describing and interpreting mathematical theorems
  • Critically assesses the theory presented within the text, as well as some of its critiques
  • Includes a web resource for teachers and students
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What People Are Saying

From the Publisher
“The book is a modern take on decision making. The innovative scope will inspire instructors by encouraging them to include a combination rather than a subset of decision-theoretic, statistical, behavioral, and philosophical concepts in their courses."
—Marzena J. Rostek, University of Wisconsin

“Written by a leading authority and teacher in the area of decision theory, this is a terrific combined textbook–handbook for students and practitioners of management. Indeed, it is a terrific book for everyone interested in ‘making better decisions.’"
—Adam Brandenburger, New York University

“This book is extremely effective for anyone who wants to acquire quick, basic understanding of old and new concepts of decision theory, with a minimum level of technical details.”
—Ehud Kalai, Northwestern University

"Gilboa is one of the leaders of the revolution that has swept through the field of decision theory in the past few decades, in which mathematical methods of statistics and economics have been integrated with findings from modern psychology. In this book he provides an accessible and practical survey of the state of the art, which encourages readers to reflect on – and try to sharpen – their intuitions and habits of decision making.  It would make an excellent primary or supplementary text for an undergraduate- or masters-level course in decision theory. It should also be useful and enjoyable reading for anyone who wants to learn about concepts that can be used and mistakes that should be avoided when taking calculated risks."
—Robert Nau, Duke University

"Itzhak Gilboa is one of the deepest thinkers in modern decision theory. In this fascinating and wonderfully written book he uses the fundamental models of decision making as a basis for reflection upon several systematic patterns revealed by our everyday choices. He strikes a nice balance between analytical models, psychological insights, and pragmatism with the end goals of improving our decision making and better understanding the decisions of others."
—Tomasz Strzalecki, Harvard University

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Product Details

  • ISBN-13: 9781444336511
  • Publisher: Wiley
  • Publication date: 10/19/2010
  • Edition number: 1
  • Pages: 232
  • Product dimensions: 6.10 (w) x 9.10 (h) x 0.90 (d)

Meet the Author

Itzhak Gilboa is a chaired Professor in the Department of Economics and Decision Sciences at HEC, Paris and in the Eitan Berglas School of Economics at Tel Aviv University, and Fellow of the Cowles Foundation at Yale University. He previously held the position of chaired Professor at the Kellogg School of Management at Northwestern University. Gilboa’s research focuses on decision under uncertainty. He has worked with David Schmeidler on axiomatic foundation of non-Bayesian decision theory and contributed to research in complexity in game theory, evolutionary game theory, and social choice. He is co-author of A Theory of Case-Based Decisions (with David Schmeidler, 2001), and author of Theory of Decision under Uncertainty (2009) and of Rational Choice (2010).
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Table of Contents

Preface.

Acknowledgments.

1. Background.

Suggested Reading.

2. Judgment and Choice Biases.

Introduction.

Problems – Group A.

Problems – Group B.

Framing Effects.

Brainstorming and Formal Models.

Endowment Effect.

Sunk Costs.

Decision Trees.

Representativeness Heuristic.

Availability Heuristic.

Anchoring.

Mental Accounting.

Dynamic Inconsistency

Exercises.

3. Consuming Statistical Data.

Introduction.

Problems.

Conditional Probabilities.

Gambler’s Fallacy.

Biased Samples.

Regression to the Mean.

Correlation and Causation.

Statistical Significance.

Bayesian and Classical Statistics.

Exercises.

4. Decisions under Risk.

Introduction.

Problems.

The Independence Axiom.

Von Neumann and Morgenstern’s Result.

Measurement of Utility.

Risk Aversion.

Prospect Theory.

Exercises.

5. Decisions under Uncertainty.

Introduction.

Problems.

Subjective Probability.

Learning From the Fact We Know.

Causality.

The Sure Thing Principle.

Alternative Models.

Objective Probabilities.

Exercises.

6. Well-Being and Happiness.

Introduction.

Problems – Group A.

Problems – Group B.

Well-Being.

Measurement Issues.

What’s Happiness?

Exercises.

Appendix A: Optimal Choice.

Appendix B: Probability and Statistics.

Solutions.

Index.

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