Correlation vs. Causation

Correlation describes the degree to which two variables tend to move together, indicating a statistical relationship. Causation, on the other hand, implies that one variable directly influences another, meaning a change in one variable produces a change in the other. While correlation can suggest a possible causal relationship, it does not prove it, as other factors might be involved. Essentially, correlation is about association, while causation is about a direct influence

Visit the following resources to learn more:

• @course@Intro to Inferential Statistics
• @article@Correlation vs. Causation | Difference, Designs & Examples
• @article@Correlation does not imply causation