
So we’ve seen a few results from looking at this graph. X and Z are generally dependent, even though there’s no causal relationship between them. This is called “confounding,” and Y is called a “confounder”. We’ve also seen that conditioning on Y causes X and Z to become statistically independent. You can simply measure this as the regression coefficient of X on Z, conditional on Y.