This ability to emulate interventions by smart observations could not have been acquired had the statistical properties of Bayesian networks not been unveiled between 1980 and 1988. We can now decide which set of variables we must measure in order to predict the effects of interventions from observational studies. We can also answer “Why?” questions. For example, someone may ask why wiggling A makes C vary. Is it really the direct effect of A, or is it the effect of a mediating variable B? If both, can we assess what portion of the effect is mediated by B?
