Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems: 9 (SpringerBriefs in Statistics, 9) - Softcover

Grover, Jeff

Softcover

ISBN 10: 1461460395 ISBN 13: 9781461460398

Publisher: Springer, 2012

Synopsis

Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes? theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes? theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes? theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes? model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes? theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences.

About this title

From the Back Cover

Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes’ theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes’ theorem, walking them through the theoretical phases of set and sample set selection, the axioms of probability, probability theory as it pertains to Bayes’ theorem, and posterior probabilities. All of these concepts are explained as they appear in the methodology of fitting a Bayes’ model, and upon completion of the text readers will be able to mathematically determine posterior probabilities of multiple independent nodes across any system available for study. Very little has been published in the area of discrete Bayes’ theory, and this brief will appeal to non-statisticians conducting research in the fields of engineering, computing, life sciences, and social sciences.

Edition details

• Publisher: Springer
• Publication date: 2012
• Language: English
• ISBN 10: 1461460395
• ISBN 13: 9781461460398
• Binding: Paperback
• Number of pages: 127