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Strategic Economic Decision-Making

Using Bayesian Belief Networks to Solve Complex Problems

  • Jeff Grover

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST, volume 9)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Jeff Grover
    Pages 49-54
  3. Jeff Grover
    Pages 55-59
  4. Jeff Grover
    Pages 61-65
  5. Jeff Grover
    Pages 67-72
  6. Jeff Grover
    Pages 73-78
  7. Jeff Grover
    Pages 79-84
  8. Jeff Grover
    Pages 85-90
  9. Jeff Grover
    Pages 91-95
  10. Back Matter
    Pages 115-116

About this book

Introduction

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.    

Keywords

Bayes' Theorem Probability Theory Statistics for Non-Statisticians

Authors and affiliations

  • Jeff Grover
    • 1
  1. 1.ELIZABETHTOWNUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-6040-4
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-6039-8
  • Online ISBN 978-1-4614-6040-4
  • Series Print ISSN 2191-544X
  • Series Online ISSN 2191-5458
  • Buy this book on publisher's site
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