It’s extremely important that epidemiologists (and for those trying to understand epidemiology) understand the difference between correlation and causation. When I teach this topic to my graduate students, I start with a classic example…When ice cream sale go up, drownings increase. Does ice cream cause drowning? No. It’s tempting to assume that one pattern causes another. However, correlation might be coincidental or it might be a result of both patterns being caused by a third factor. The third variable here is a hot summer day, which boosts ice cream sales AND swimming, and thus drownings. In other words, correlation (ice cream sales and drownings) does not imply causation (ice cream sales cause drownings).
Deaths and the vaccine…
Deaths and the vaccine…
Deaths and the vaccine…
It’s extremely important that epidemiologists (and for those trying to understand epidemiology) understand the difference between correlation and causation. When I teach this topic to my graduate students, I start with a classic example…When ice cream sale go up, drownings increase. Does ice cream cause drowning? No. It’s tempting to assume that one pattern causes another. However, correlation might be coincidental or it might be a result of both patterns being caused by a third factor. The third variable here is a hot summer day, which boosts ice cream sales AND swimming, and thus drownings. In other words, correlation (ice cream sales and drownings) does not imply causation (ice cream sales cause drownings).