the process of identifying cause-and-effect relationships between variables with statistics. The goal is to determine whether a change in one variable causes a change in another variable, ruling out alternative explanations
This usually involves intervention in the variables to change another variable, which is absent in predictive inference. However, counterfactual can be filled using statistical models to calculate average treatment effect.