Correlation

In statistics and probability theory, correlation is how similar two sets of data are.^[1] This relationship means that if one set of data changes, the other will change as well (at least more commonly than if it were up to pure chance).

Correlation does not always mean that one causes the other. In fact, it is very possible that there is a third factor involved. Correlation can have one of two directions: Positive or negative. If it is positive, then the two sets go up together. If it is negative, then one goes up while the other goes down. Lots of different measurements of correlation are used for different situations. For example, on a scatter graph, people draw a line of best fit to show the direction of the correlation.

Correlation can be measured through correlation coefficients. The most common correlation coefficients are Pearson correlation coefficient and Spearman's rank correlation.

Correlation is useful in real life. An example of correlation is the height of a parent and their children.

1. ↑ "Correlation and Causation - easily explained! | Data Basecamp". 2021-11-27. Retrieved 2022-07-01.