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Making Decisions, by Dennis V. Lindley
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Making Decisions Second Edition D.V. Lindley Formerly Professor of Statistics, University College London This book looks at the problems involved in decision-making and argues that there is only one logical way to make a decision. By the use of three basic principles--assigning probabilities to the uncertain events; assigning utilities to the possible consequences; and choosing that decision that maximizes expected utility--decisions can be reached more efficiently and with less disagreement. It shows that only maximization of expected utility leads to sensible decision-making. This extensively revised second edition uses only elementary mathematics and will be of interest to all those concerned with decision-making and its consequences. Since his retirement from University College London in 1977 Professor Lindley has held visiting appointments at Berkeley, University of Florida, George Washington University, University of Sao Paulo, University of Wisconsin, Monash University, Australia, and University of Canterbury, New Zealand. Contents
* Decisions and uncertain events
* A numerical measure for uncertainty
* The laws of probability
* A numerical measure for consequences
* The utility of money
* Bayes' Theorem
* Value of information
* Decision trees
* The assessment of probabilities and utilities
* An appreciation
Appendix Answers to exercises Glossary of Symbols Subject Index
- Sales Rank: #2789017 in Books
- Published on: 1985-12-23
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.92" h x .59" w x 6.85" l,
- Binding: Hardcover
- 220 pages
From the Back Cover
Making Decisions Second Edition D.V. Lindley Formerly Professor of Statistics, University College London This book looks at the problems involved in decision-making and argues that there is only one logical way to make a decision. By the use of three basic principles—assigning probabilities to the uncertain events; assigning utilities to the possible consequences; and choosing that decision that maximizes expected utility—decisions can be reached more efficiently and with less disagreement. It shows that only maximization of expected utility leads to sensible decision-making. This extensively revised second edition uses only elementary mathematics and will be of interest to all those concerned with decision-making and its consequences. Since his retirement from University College London in 1977 Professor Lindley has held visiting appointments at Berkeley, University of Florida, George Washington University, University of Sao Paulo, University of Wisconsin, Monash University, Australia, and University of Canterbury, New Zealand. Contents
Most helpful customer reviews
34 of 34 people found the following review helpful.
Lindley expouses the Bayesian approach to decision theory
By Michael R. Chernick
Dennis Lindley is a strong believer in the subjective approach to probability that is called Bayesian. He has written texts on probability and statistics that presents strong arguments for why he believes it is the only correct way to formulate a theory of probability and to coherently apply probabilty to problems in statistical inference.
Statistical decision theory developed in the 1940s and 1950s as a way to incorporate statistical methods in general decision making processes. Abraham Wald helped develop the classical (frequentist) approach to this in the late 1940s.
Frequentist and Bayesian approaches have then developed in the 20th Century. In this book Lindley uses a basic urn model for probability as a starting point for an elementary introduction into the Bayesian approach to decision making. He presents the basics of utility theory which is the Bayesian approach to scoring potential decisions, so as to determine the "best" decision.
1 of 1 people found the following review helpful.
decision making is an good approach to teach statistics
By Josue Guzman-Torres
This is a must-read book for all statisticians; decision making is an good approach to teach statistics. The author emphasises the role of Bayes rule, and offers several examples as applications; most chapters end with various exercises.
The approach followed by the author is introductory; and can be read by non statisticians without any difficulty.
2 of 33 people found the following review helpful.
What an awful book...
By A Customer
I'm currently a student at the University of California, San Diego. I feel that this book is an awful piece of writing that does not explain things clearly. Many of my colleagues feel that this is one of the most awful books that have been forced on us as well.
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