Causal Inference Theory

Causal Inference Theory is a framework used to determine whether one event or condition (the cause) directly affects another (the effect). It helps us understand relationships between variables beyond mere correlation. For example, just because two things occur together doesn’t mean one causes the other. Causal inference uses methods like experiments or statistical models to establish cause-and-effect relationships, helping researchers make informed decisions in fields like medicine, economics, and social sciences. Essentially, it provides a systematic way to identify and validate the reasons behind observed outcomes.