Statistical methodology and its difficulty for causal inference are first reviewed in experimental, quasi-experimental or observational studies. The review includes path analysis,graphical modeling, Rubin's counterfactual models and propensity scores. It is then studied how those statistical methods can relate with causal discovery in data mining in computational science.