Intro to Biostatistics
A Bayesian network is a graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Each node in the graph corresponds to a random variable, and the edges represent the conditional dependencies between these variables, making it a powerful tool for modeling uncertainty and reasoning under uncertainty. This concept is deeply tied to Bayes' theorem, which provides a way to update probabilities as new evidence is presented.
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