Spurious Correlation
Two variables can trace strikingly similar paths without either causing the other. A matched curve is a reason to investigate, not a causal explanation.
American cheese consumption rises and falls alongside Google’s stock price. The curves may invite a story, but any claim that cheese moves the share price—or that Google drives cheese consumption—collapses into absurdity.
E1The story arrives after the pattern
With enough variables and enough time periods, some pairs will move together by coincidence or because each follows an unrelated background trend. Once you notice a visual match, your mind can reverse-engineer a persuasive narrative connecting them. The correlation is real as a pattern in the selected data; the invented causal pathway is not. That is why correlation does not imply causation: causality requires evidence about direction and mechanism beyond two synchronized curves.
E1Correlation is still a clue
Calling a correlation spurious is not proof that no connection exists. The pattern may reflect coincidence, a hidden common cause, or an undiscovered mechanism. The model blocks premature causal certainty; it does not settle the underlying question.
Write the missing causal chain
Tomorrow, when a chart pairs two moving variables, write the proposed chain from one to the other in explicit steps. Then name what evidence would distinguish that chain from coincidence, a hidden common cause, and a reversed arrow. If you cannot do that, describe the result as a correlation—not an explanation.
Episodes that teach this
-
The Great LIE - Correlation is Not Causation - FutureIQ
· explained at 2:14
7,309 views
American cheese consumption correlates with Google stock price, but the implied causal stories are absurd.