Data Science and Machine Learning Applications

Causal Inference

This is a method used to determine cause-and-effect relationships from data. Unlike correlation, which merely identifies associations, causal inference seeks to understand how changes in one variable directly impact another. It often involves techniques like randomized controlled trials (RCTs), natural experiments, and statistical models to control for confounding factors. This approach helps in making more informed decisions and understanding the underlying mechanisms driving observed phenomena.