Causality in Statistics

Causality in statistics refers to the relationship between two variables where a change in one directly results in a change in the other. It's about understanding whether and how one factor influences another, rather than just being related or associated. Establishing causality typically requires careful study design and evidence to rule out other explanations. For example, if increasing exercise consistently leads to weight loss, we might say exercise causes weight loss, assuming other factors are controlled. Recognizing causality helps in making informed decisions, policies, or interventions based on understanding what actually produces an effect.