The strength of the correlation is determined by the correlation coefficient, r. It is sometimes referred to as the Pearson product moment correlation coefficient in honor of its discoverer, Karl Pearson, who first introduced the term in 1900. There are three different formulas used to calculate this number: the raw score formula, the deviation formula or the covariance formula.

The correlation coefficient measures the degree of a linear relationship between two variables. These variables are usually labeled X and Y. Correlation is similar to regression, but different in how it relates two variables to one another. Regression is concerned with using one variable to predict another. Correlation looks at the relationship between the two variables. The correlation coefficient has either a positive or a negative sign. The sign describes the direction of the relationship between the two variables. A positive sign and a positive correlation coefficient indicates that when the value of one variable increases, the value of the other increases as well. Similarly, if the value of one variable decreases, the value of the other variable decreases if the correlation coefficient is positive. If the correlation coefficient is negative, when the value of one variable increases, the value of the other variable decreases and vice versa.