Discussion
What does a Bayesian network represent?
Answer: D
The network encodes a joint distribution as a product of conditional distributions, one per node given its parents, with the graph asserting the conditional independences. It is often drawn causally because that gives the sparsest structure, but the mathematics requires only that the independences hold. Rules with certainties and pairwise correlations are different formalisms. Separating what the network asserts from why it is usually drawn that way avoids claiming more than the formalism supports.
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