Correlation vs. Causation: Don’t Confuse Coincidence With Cause

One of the easiest mistakes in reasoning is assuming that because two things happen together, one must have caused the other.

That is the difference between correlation and causation.

Correlation

Correlation means two variables are related in some way. People who exercise more, for example, may report better health. There is an association, but that alone does not tell us why.

Causation

Causation means that a change in one thing contributes to a change in another. Saying that increasing physical activity contributes to certain health improvements is a much stronger claim.

The classic problem

Imagine researchers discover that people who carry umbrellas are more likely to get wet. Does carrying an umbrella cause people to get wet?

Obviously not. Rain causes both umbrella use and getting wet. The two are correlated because of a third factor.

Another example

Suppose ice cream sales increase when drowning deaths increase. Does eating ice cream cause drowning? No.

Hot weather can increase ice cream sales and swimming. More swimming can create more opportunities for drowning incidents.

The variables move together, but one does not necessarily cause the other.

Why this matters

You see correlations everywhere: social media use and anxiety, education and income, exercise and health, sleep and productivity, technology use and behavior.

The important question is:

Researchers use controlled experiments, longitudinal studies, statistical methods, and other approaches to investigate causal relationships.

Takeaway

Whenever two things appear together, do not immediately conclude that A caused B. First ask whether something else could be causing both.

Correlation can be a clue. It is not automatically proof of causation.