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" ... Bayesian Networks are applicable to cause and effect problem domains. BBN's are aimed at probabilities of the relationship between symptoms and situations or outcomes. This is accomplished by mapping the casual probabilistic relationship among a set of random variables, the conditional dependencies, and joint probability distribution. This is mapping is often represented in a visual model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Keep in mind BBNs are dependent on having good statistics to drive results. ... "