 But even if we do not have a complete SEM, we can often compute the effect of interventions. Suppose we have a causal model in which the probability distribution P satisfies MC on the causal DAG \(\bG\) over the variable set \(\bV = \{X_1, X_2 ,\ldots ,X_n\}\). The most useful version of MC for thinking about interventions is MCFactorization (see  Section 4.2),  which tells us: