Many people mistake correlation for causation. If they see two sets of data moving together, they may think that A caused B. In reality, they might just be coincidentally synchronized, or there could be a third common factor behind both. The next time you encounter this kind of phenomenon, first distinguish between correlation and causation—don’t jump to conclusions.