Learn what distinguishes a simple regression model from a multiple regression model, and how to choose the best one for your data and question.

Learn how to determine the right variables for your regression model with our data analytics guide on feature selection and testing.

Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

At times it is desirable to have independent variables in the model that are qualitative rather than quantitative. This is easily handled in a regression framework. Regression uses qualitative ...

Learn how to graph linear regression in Excel. Use these steps to analyze the linear relationship between an independent and a dependent variable.

Regression Analysis Basics In its most rudimentary form, regression analysis is the estimation of the ratio between two variables.

Next, specify the linear regression model with a MODEL statement. The MODEL statement in PROC TSCSREG is specified like the MODEL statement in other SAS regression procedures: the dependent variable ...

The beta regression is a widely known statistical model when the response (or the dependent) variable has the form of fractions or percentages. In most of the situations in beta regression, the ...