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Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship between one dependent variable and one or more independent variables.
The process for performing multiple linear regression follows the same pattern that simple linear regression does: 1  Gather the data for the Xs and the Y. 2  Estimate the multiple linear regression coefficients. When you have more than one X variable, the equations for deriving the Î²s become very complex and very tedious.