 In realistic scientific cases, we never directly observe the true probability distribution P over a set of variables. Rather, we observe finite data that approximate the true probability when sample sizes are large enough and observation protocols are well-designed. Since our primary concern is with the philosophical issue of how probabilities determine or constrain causal structure, we will not address these important practical concerns. An answer to a query that can be determined from the true probabilities is said to be identifiable. For instance, if we can determine the correct DAG on a variable set \(\bV\) from the probability distribution on \(\bV\), the DAG is identifiable.