Type 1 and type 2 represent the same statistical dependencies (i.e., formula_3 and formula_14 are independent given formula_4) and are, therefore, indistinguishable within purely cross-sectional data. Type 3, however, can be uniquely identified, since formula_3 and formula_14 are marginally independent and all other pairs are dependent. Thus, while the "skeletons" (the graphs stripped of arrows) of these three triplets are identical, the directionality of the arrows is partially identifiable. The same distinction applies when formula_3 and formula_14 have common ancestors, except that one must first condition on those ancestors. Algorithms have been developed to systematically determine the skeleton of the underlying graph and, then, orient all arrows whose directionality is dictated by the conditional independencies observed.