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This article explores the key differences between observational and experimental studies, particularly in the context of drug testing and use. It discusses how observational methods identify associations but do not establish causality, while experimental methods involve interventions to determine effects. It also addresses the implications of non-perfect associations in research, emphasizing that a lack of perfect correlation does not necessarily imply a causal relationship. Lastly, it examines the importance of case selection in establishing valid conclusions in research.
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