The Pearson correlation coefficient is used to measure the strength of a linear association between two variables,
where the value *r* = 1 means a perfect positive correlation and the value
*r* = -1 means a perfect negataive correlation. So, for example, you could
use this test to find out whether people's height and weight are correlated (they
will be - the taller people are, the heavier they're likely to be).

*Requirements for Pearson's correlation coefficient*

- Scale of measurement should be interval or ratio
- Variables should be approximately normally distributed
- The association should be linear
- There should be no outliers in the data

*Equation*