Effects of Causes and Causes of Effects

We describe and contrast two distinct problem areas for statistical causality: studying the likely effects of an intervention (effects causes) whether there is a causal link between observed exposure outcome in individual case (causes effects). For each these, we introduce compare various formal frameworks that have been proposed purpose, including decision-theoretic approach, structural equations, stochastic models, potential outcomes. argue counterfactual concepts are unnecessary causes but needed analyzing effects. They are, however, subject to degree arbitrariness, which can be reduced, though not general eliminated, by taking account additional structure problem.