This post has a big problem in that “cause” and “effect” are totally the wrong words, because when calculating joint probabilities you don’t need to know causal information at all.
Causality, or whatever way of making it directed and acyclic feels natural. If you have statistical observations but no causal information, you’re best off, e.g., just going from left to right.
This post has a big problem in that “cause” and “effect” are totally the wrong words, because when calculating joint probabilities you don’t need to know causal information at all.
P(x,y,z) = P(x) P(y|x) P(z|xy) = P(x) P(z|x) P(y|xz) = P(y) P(x|y) P(z|xy) = P(y) P(z|y) P(x|zy) = P(z) P(y|z) P(x|zy) = P(z) P(x|z) P(y|xz).
OK, you’re right. You only need to think about causality if you don’t want your graph to be fully connected.
Causality, or whatever way of making it directed and acyclic feels natural. If you have statistical observations but no causal information, you’re best off, e.g., just going from left to right.