Karl pearson correlation formula

Measure of linear correlation

Not to be confused with Coefficient of determination.

In statistics, the Pearson correlation coefficient (PCC)^[a] is a correlation coefficient that measures linear correlation between two sets of data.

It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1.

As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations. As a simple example, one would expect the age and height of a sample of children from a primary school to have a Pearson correlation coefficient significantly greater than 0, but less than 1 (as 1 would represent an unrealistically perfect correlation).

Naming and history

It was developed by Karl Pearson from a related id