ABSTRACT
Like correlation analysis, simple linear regression is a technique that is used to explore the nature of the relationship between two continuous random variables. The primary difference between these two analytical methods is that regression enables us to investigate the change in one variable, called the response, which corresponds to a given change in the other, known as the explanatory variable. Correlation analysis makes no such distinction; the two variables involved are treated symmetrically. The ultimate objective of regression analysis is to predict or estimate the value of the response that is associated with a fixed value of the explanatory variable.
