Regression analysis is an analytical technique that examines the relationship between more than one independent variable and one dependent variable. In comparison, correlation explains the relationship between one independent variable and one dependent variable. Three types of regression are logistic regression, linear regression, and supervised learning.

With regression analysis, you can obtain a measure of the effect each independent variable has on the dependent variable. The relationship between the variables is stated as an equation for a line or curve. The measurement is expressed as a coefficient of the independent variable.

Regression Analysis Example

A problem where you might consider using regression analysis is where you want to measure the impact on cigarette sales of a change in cigarette taxes. Once you have determined the coefficient, you can see how strong or weak the causal relationship between these two variables. Regression analysis is designed to reduce the importance of random chance.

With the many different types of regression analysis, it is important to select the correct one for your data. Each model has specific criteria that must be met in order to use it. One way to ensure that you are using the correct model is by conferring with a statistical consultant.