Explaining junctions using correlation, independence and regression to understand their critical importance in causal inference — Introduction Causal inference is the application of probability, visualisation, and machine learning in understanding the answer to the question “why?” It is a relatively new field of data science and offers the potential to extend the benefits of predictive algorithms which address the symptoms of an underlying business problem to permanently…