Distinguishing correlation from a shared cause
Launch library · evergreen read
Two things rising together does not mean one is causing the other. Ice cream sales and drowning incidents both increase in summer, not because ice cream causes drowning, but because a third factor, warm weather, drives both independently. This kind of shared cause is one of the most common traps in reading any statistic.
Spotting it requires asking a simple question: is there a plausible reason the first thing would directly cause the second, or is there a more obvious factor that would explain both at once. Often, a little thought reveals a shared cause sitting quietly behind two figures that look, at a glance, like they must be connected.
This is not a reason to dismiss every correlation, since some genuinely do reflect cause and effect. It is a reason to treat a correlation as a starting question rather than a finished answer, and to keep looking for the mechanism before accepting the more dramatic explanation.