Correlation indicates a relationship between two variables, while causation implies that one directly causes the other.
Confusing the two leads to faulty conclusions.
Examples in Action
- Assuming performance changes caused by unrelated events
- Misinterpreting coincidental trends
- Acting on patterns without validation
- Drawing conclusions without controls
Typical Outcomes / Results
- Reduced false conclusions
- Stronger experimentation discipline
- Improved confidence in decisions
- Better prioritisation
This definition reflects foundational analytical reasoning.