Key Terms

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 points
The 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