Definition
A mathematical relationship in which two or more events or variables are associated but not causally related, often due to either coincidence or the presence of a certain third, unseen factor (a confounding variable).
Why It Matters
Spurious correlations are the ‘hallucinations’ of data analysis; identifying them is the only way to avoid the ‘post hoc’ trap of assuming that because two trends move together, one must cause the other, a critical skill for avoiding false conclusions in science and policy.
Core Concepts
- Correlation does not imply causation: Two trends moving together doesn’t mean one causes the other.
- Confounding Variables: An unmeasured third variable that influences both the supposed cause and the supposed effect.
- P-Hacking: Manipulating data or analyses until non-significant results become significant.