Now we come to the second, and perhaps more important, impact of Bayesian networks on causal inference. The relationships that were discovered between the graphical structure of the diagram and the data that it represents now permit us to emulate wiggling without physically doing so. Specifically, applying a smart sequence of conditioning operations enables us to predict the effect of actions or interventions without actually conducting an experiment.
