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This book is an extension of the author's first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN). It walks the learner through the steps of fitting and solving fifty BBN numerically, using mathematical proof. The author wrote this book primarily for inexperienced learners as well as professionals, while maintaining a proof-based academic rigor.

The author's first book on this topic, a primer introducing learners to the basic complexities and nuances associated with learning Bayes' theorem and inverse probability...

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, walkingthem 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...