# Strategic Economic Decision-Making

## Using Bayesian Belief Networks to Solve Complex Problems

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

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

*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.

Bayes' Theorem Probability Theory Statistics for Non-Statisticians

- 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
- About this book

- Industry Sectors
- Biotechnology
- Pharma