The correlation coefficient, usually denoted by $r,$ measures the direction and strength of a linear relationship between two variables. It can take on values between $\text{-}1$ and $1.$ Values near $\text{-}1$ mean that the correlation is strong and negative, while values close to $1$ are strong and positive. Values close to $0$ represent a weak or very weak correlation, but $r=0$ represents no correlation. When there is a linear model that describes the relationship between two variables well, the correlation coefficient indicates how close the points are to the line of best fit. The closer the value $r$ is to $\text{-}1$ or $1,$ the closer the points to the line of best fit. Keep in mind that the correlation coefficient is useful only when a linear model describes the data well. In addition to understanding the meaning of the correlation coefficient, while a graphing calculator is able to find the line of best fit, it is beneficial to learn how to calculate it by hand. Consider the following formula.