CAUSALITY: USING MATH TO UNDERSTAND THE SCIENCE OF CAUSE AND EFFECT.

This article explores the concept of causality and its importance in various fields of science and society. Causality refers to the relationship between a cause and an effect, where the effect is a result of the cause. The article explains that causality is studied using mathematical tools such as probability, statistics, and graph theory. It also highlights the difference between correlation and causality, emphasizing that correlation does not imply causation. Understanding causality allows scientists to make predictions, develop treatments, and understand complex systems. The article concludes by discussing the Rubin causal model, which provides a method for estimating causal effects in experiments. [Extracted from the article]