Ex-post facto analysis, also known as correlational analysis, primarily relies on which approach?

Ex-post facto analysis, also known as correlational analysis, primarily relies on which approach?

• A. Use of statistical analysis to control for the effect of a given variable.
• B. Random assignment to groups.
• C. Manipulation of the independent variable.
• D. Establishing causation.

Answer: (A)

Ex-post facto analysis looks for relationships in data after events have occurred, so there’s no random assignment or manipulation of variables. The core approach is using statistical analysis to control for the effects of other variables, allowing researchers to see whether an association between variables persists when potential confounders are held constant. This is why this option is the best choice: it reflects examining relationships by adjusting for influences rather than experimenting or proving causation. Random assignment and manipulation belong to experimental designs, not ex-post facto analyses. And establishing causation isn’t the aim here; correlational work identifies associations, not causal direction.

Ex-post facto analysis looks for relationships in data after events have occurred, so there’s no random assignment or manipulation of variables. The core approach is using statistical analysis to control for the effects of other variables, allowing researchers to see whether an association between variables persists when potential confounders are held constant. This is why this option is the best choice: it reflects examining relationships by adjusting for influences rather than experimenting or proving causation. Random assignment and manipulation belong to experimental designs, not ex-post facto analyses. And establishing causation isn’t the aim here; correlational work identifies associations, not causal direction.