Title text: Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'.
This comic focuses on the difficulty of many people to grasp the difference between correlation and causation. When two variables (like death and age) are highly correlated, many often make the assumption that one is leading to the other. However, this is not always the case.
Take for example a scenario where a number of people are wearing sunglasses and a number of people are getting sunburned are highly correlated. Here it would seem silly to believe that wearing sunglasses causes sunburns or that getting sunburned causes wearing sunglasses. In this case, both are caused by a third factor (specifically that it is sunny).
This is because when two variables are correlated it does not provide evidence that one variable has caused the other. They are merely correlated, or their trends move in relation to each other. A positive correlation would mean that as one variable increases so does the other, while a negative correlation means that as one variable increases the other decreases.
In this situation Cueball is explaining to Megan his realization that correlation is not the same thing as causation. He further explains that his belief changed after taking a statistics class. Megan, however, then makes the seemingly obvious leap and declares that his realization was the result of taking the statistics course. Cueball’s final response of “Well, Maybe.” is fitting because there is no way to know if the statistics class caused his opinion to change or, instead, the two are merely correlated, as many variables would have changed during that semester, each of which could have potentially influenced his view of the topic. In order to determine causation a control group is required, which experiences all of the same variables as the experimental group minus the one variable that you believe is responsible for the change.
The image text is referring to the idea that while correlation does not mean causation, it does often enough that it makes the distinction blurry for non-scientists. For example, in this case the statistics course is a likely candidate for leading to his change in knowledge. Well, maybe.
- [Cueball is talking to Megan.]
- Cueball: I used to think correlation implied causation.
- Cueball: Then I took a statistics class. Now I don't.
- Megan: Sounds like the class helped.
- Cueball: Well, maybe.