= Judea Pearl
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<Judea Pearl> developed graphical methods for probabilistic and causal reasoning. His account of <D-separation> explains how the orientation of arrows in a <directed acyclic graph> determines <conditional independence>[conditional independences] implied by its factorization assumptions.<D-separation without tears by Judea Pearl>[§§1,1.2–1.3]{ref}
For a chain $X\to Z\to Y$, conditioning on $Z$ blocks the path. For a <collider> $X\to Z\leftarrow Y$, the path is blocked before conditioning, but conditioning on $Z$ or an appropriate descendant can activate it. A graphical separation guarantees <independence> for distributions obeying the graph's assumptions; an unblocked path does not force dependence in every numerical parameterization. These distinctions make the graph a reasoning tool rather than just a picture of observed <correlation>[correlations].
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