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In this short note, I derive the Bell-CHSH inequalities as an elementaryresult in the present-day theory of statistical causality based on graphicalmodels or Bayes' nets, defined in terms of DAGs (Directed Acyclic Graphs)representing direct statistical causal influences between a number of observedand unobserved random variables. I show how spatio-temporal constraints inloophole-free Bell experiments, and natural classical statistical causalityconsiderations, lead to Bell's notion of local hidden variables, and thence tothe CHSH inequalities. The word "local" applies to the way that the chosensettings influence the observed outcomes. The case of contextualsetting-dependent hidden variables (thought of as being located in themeasurement devices and dependent on the measurement settings) is automaticallycovered, despite recent claims that Bell's conclusions can be circumvented inthis way.

Bell's theorem is an exercise in the statistical theory of causality