For observational data, correlations can't confirm causation... Correlations between variables show us that there is a pattern in the data: that the variables we have tend to move together. However, correlations alone don't show us whether or not the data are moving together because one variable causes the other.

Why can't correlations be used to prove causation?

Causation is the relationship between cause and effect. So, when a cause results in an effect, that's a causation. ... When we say that correlation does not imply cause, we mean that just because you can see a connection or a mutual relationship between two variables, it doesn't necessarily mean that one causes the other.

Why correlation is not causation example?

"Correlation is not causation" means that just because two things correlate does not necessarily mean that one causes the other. As a seasonal example, just because people in the UK tend to spend more in the shops when it's cold and less when it's hot doesn't mean cold weather causes frenzied high-street spending.