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Regression that includes two or more non-constant independent variables.

For two or more dependent variables, use .

Linear regression models a variable (the "dependent variable") as varying randomly with respect to a linear combination of other variables (the "independent variables"). Multiple regression includes two or more non-constant independent variables (three or more variables in total). This adds complications not present with only one independent variable, including complex forms of correlation and interaction effects.

Use this multiple-regression tag instead of the more generic regression tag when your question focuses on an issue specifically related to including two or more independent variables in a regression model.

Multiple regression concerns the so-called "general linear model," not to be confused with the generalized linear model despite the close similarity of their names.