In a statistical analysis, what is generally necessary to establish a causative relationship?

Establishing a causative relationship in statistical analysis requires correlation and temporal precedence. Correlation indicates that there is a relationship between two variables, meaning when one variable changes, the other tends to change as well. However, correlation alone does not imply causation; it does not address whether one variable actually causes the change in the other or if other factors are involved.

Temporal precedence is crucial because it establishes the order in which events occur. For a causation claim to be valid, the cause must occur before the effect. Without demonstrating that the independent variable precedes the dependent variable in time, one cannot conclusively claim that a causal relationship exists. Therefore, both correlation and temporal precedence must be shown to support a robust inference of causality in research.