Which of the following is a criterion for establishing causality?

Establishing a correlation between variables is a fundamental criterion for establishing causality. In research, demonstrating that two variables are correlated means that as one variable changes, the other variable also experiences a change in some systematic way. This relationship is often the first step in suggesting a potential causal link. However, correlation alone does not imply causation; it is necessary to conduct further analysis to rule out other factors and establish a more direct cause-and-effect relationship.

While longitudinal studies, which allow researchers to observe changes over time, can strengthen causal claims by examining how variable relationships evolve, the initial step in any causal analysis involves showing that a correlation exists between the variables in question. Hence, identifying correlation is crucial for building a foundation for further causal inference.

Qualitative data, while valuable for insights and understanding context, does not serve as a standalone criterion for establishing causality. Furthermore, restricting data collection to one sample limits the ability to generalize findings or examine relationships across different contexts or populations, making it less effective for establishing causation.