Correlation vs Causation is a key topic for anyone learning statistics, machine learning, or data interpretation. Two variables may move together because of coincidence, a common influencing factor, or a genuine causal link. Examining these possibilities helps data professionals understand relationships more carefully and avoid confusing statistical patterns with direct causes.
