Directed acyclic graphs (DAGs) are a type of graph used to represent relationships among variables, where edges have a direction and there are no cycles. This means that the graph flows in one direction and you cannot return to the same node, making it particularly useful in probabilistic modeling. In the context of Bayesian statistics, DAGs help to visualize dependencies between random variables and facilitate the understanding of conditional independence.
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