The Difference Between Correlation and Causation
The educational channel Sprouts explains the difference between correlation and causation, noting that one does not imply the other.
In statistics, we must differ between correlation and causation. Correlation means two things move together at the same time. Causation means one thing causes a change in the other.
The narrator observes that our brains like simple answers, but that often leads to errors in interpretation.
Our brains love simple stories, such as X causes Y. This is why when we see a strong correlation, say kids’ shoe size and reading ability, We may think of causation. But three solutions help us avoid these errors.
The errors include confounding factors, reverse causality, and spurious correlation.
As kids grow, they need larger shoe and get better at reading. If a third factor drives correlating results, we call it confounding. Then there is reversed causality. We may think that ice cream makes people happy, but maybe happy people just have more reasons to buy ice cream? … Spurious correlation exists when patterns appear by chance. For example: as the number of pirates decreased, we recorded increasingly hotter days—but there’s no plausible common cause.
