Machine Learning, Causal Inference, Data Science, Time Series Analysis, Statistics.
This is often good enough for making predictions, but it is insufficient when it comes to understanding causes and effects (i.e., the why or what if). This is simply because correlation does not imply causation. In many real-world cases, however, we actually find ourselves more interested in