Of course, at times scientists do not know the entire web of relationships between their variables. In that case, Wright argued, we can use the diagram in exploratory mode; we can postulate certain causal relationships and work out the predicted correlations between variables. If these contradict the data, then we have evidence that the relationships we assumed were false. This way of using path diagrams, rediscovered in 1953 by Herbert Simon (a 1978 Nobel laureate in economics), inspired much work in the social sciences.
This is a fantastic idea; and should really be used and taken into consideration when dealing with big data, though i'm curious as to how one can infer what correlations to expect..
