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With a correlational design, why should we be cautious in drawing causal conclusions?

With a correlational design, why should we be cautious in drawing causal conclusions?

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Correlation measures the relationship between two variables.Variables are measured and the strength of the association between them is calculated. Naturalistic observation and surveys also are often used to examine associations between variables

Correlation research only uncovers a relationship; it cannot provide a conclusive reason for why there's a relationship. A correlative finding doesn't reveal which variable influences the other. For example, finding that wealth correlates highly with education doesn't explain whether having wealth leads to more education or whether education leads to more wealth. Reasons for either can be assumed, but until more research is done, causation can't be determined. Also, a third, unknown variable might be causing both. For instance, living in the state of New York can lead to both wealth and education.

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