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Making Better Decisions: Decision Theory in Practice

توضیحات

Making Better Decisions: Decision Theory in Practice introduces readers to some of the principal ideas from decision theory and examines how they might help us make better decisions.

The presentation is designed to appeal to students and the general reader; based on problems, readers are encouraged to imagine a situation, and then make a decision or a judgment. The problems are chosen to exemplify some principles developed in decision theory, as well as violations of these principles derived from the psychological literature. 

Making Better Decisions offers explanations of both the theories we would like to adopt in order to make better decisions, and the theories that explain how those around us behave. In doing so, the book presents crucial insights into the decision-making process that can influence and change our behavior and our ability to interact with those around us.


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).
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.