What does causal inference aim to establish?

Causal inference aims to establish cause-and-effect relationships, which is foundational to understanding how one variable influences another. This involves rigorous methods and frameworks that help researchers determine whether a change in one variable leads to a change in another, rather than simply observing correlations or patterns. Establishing causality is vital in fields such as social sciences, epidemiology, and economics because it allows for predictions and interventions based on identified relationships.

While other answers touch on aspects of data analysis, they do not reach the depth and focus required for understanding causal inference. Observing patterns or trends in data alone doesn’t clarify whether one variable is responsible for changes in another. Similarly, statistical correlations may indicate an association but do not imply a direct cause-and-effect relationship, which is the central goal of causal inference. Thus, the precise aim of causal inference is to understand and demonstrate the mechanisms through which one factor affects another.