ABSTRACT
Regression is widely used as a quantitative approach to data analysis. It is a model of prediction that is both simple and flexible, leading to a long history of widespread use across disciplines. There are many different types of regression, but multiple linear regression is the most common and is usually the first regression technique people learn. Multiple linear regression looks at the association between one dependent variable and at least one independent variable. Typically, it looks at the relationship between one dependent variable and several independent variables. This analytic tool can be used for several purposes. Multiple regression is closely related to analysis of variance (ANOVA) tests. ANOVA tests are appropriate when the independent variables are categorical, while multiple regression can test variables that are continuous. Regression also includes control variables. These variables are said to "control for" demographic characteristics.
