When two variables are analyzed in an observational study, the relationship is best described as:

• A. Causation
• B. Association
• C. Control
• D. Pattern

Answer: (B)

In observational research, relationships between two variables are described as associations rather than causation. Because there’s no random assignment or controlled intervention, the observed link could be driven by other factors, bias, or reverse causation, so you can’t prove that one variable causes the other. For example, if higher exercise is linked to lower blood pressure, other lifestyle factors or measurement issues might explain the connection. The term association acknowledges that the variables move together but stops short of claiming that one causes the other, which is why it’s the best description for observational data. Causation implies a true cause-and-effect relationship that observational studies alone can’t establish, while “control” and “pattern” don’t precisely describe the nature of the relationship.