What is true about causation in relation to correlation?

Causation always implies correlation because if one event causes another, there must be a statistical relationship between the two. This means that changes in the cause should lead to changes in the effect. For example, if a new medication effectively reduces symptoms of a disease, there will be a correlation observed between medication use and symptom relief.

However, correlation alone does not imply causation, as there can be other factors influencing both the cause and the effect. It's important to distinguish that while causation requires the observation of correlation, correlation does not prove that one event causes another. Thus, recognizing that causation inherently involves correlation helps to understand the foundational principles in fields like biomedical engineering, where establishing clear relationships is crucial for research and applications.