  We provide a conceptual map to navigate causal analysis problems. Focusing on
the case of discrete random variables, we consider the case of causal effect
estimation from observational data. The presented approaches apply also to
continuous variables, but the issue of estimation becomes more complex. We then
introduce the four schools of thought for causal analysis
