- coefficient of correlation
- a measure developed by Karl Pearson during the early 1900s that gives the strength of association between the independent variable and the dependent variable;
$$r=\frac{n{{{\displaystyle \sum}}^{\text{}}}^{\text{}}xy-[{{{\displaystyle \sum}}^{\text{}}}^{\text{}}x][{{{\displaystyle \sum}}^{\text{}}}^{\text{}}y]}{\sqrt{(n{{{\displaystyle \sum}}^{\text{}}}^{\text{}}{x}^{2}-{[{{{\displaystyle \sum}}^{\text{}}}^{\text{}}x]}^{2})(n{{{\displaystyle \sum}}^{\text{}}}^{\text{}}{y}^{2}-{[{{{\displaystyle \sum}}^{\text{}}}^{\text{}}y]}^{2})}}$$where
*n*is the number of data pointsThe coefficient cannot be more than 1 and less than –1. The closer the coefficient is to ±1, the stronger the evidence of a significant linear relationship between

*x*and*y*.

- outlier
- an observation that does not fit the rest of the data