ABSTRACT
This chapter concerns the concept called correlation. Correlation has a descriptive nature: it is a method for describing the relationship that might or might not exist between two or more variables. In 1895, Karl Pearson—based on previous work by his mentor, Sir Francis Galton—devised the Pearson product-moment (PPM) correlation coefficient, also called simply Pearson's r. The PPM correlation coefficient has many uses in science. It describes three of the most important ones here: determining relationships, examining the reliability and validity of measurements, and prediction. Now that authors examined pictorial representations depicting the relationship between two variables, they turn to the calculation of r. Following are three ways to approach the interpretation of a particular value of r: verbal description, the coefficient of determination, and statistical significance. The amount of prediction error resulting from a line of best fit is a function of the correlation coefficient and the variability in the X and Y variables.
