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Linear Regression Definition

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Linear Regression Definition

Linear regression is generally defined as having an output variable, usually labeled Y and at least one input variable, usually labeled X (if more than one input variable, the labels would be X1, X2, X3, etc.). Output variable Y is scalar. Linear regression is a predictive model in which output variable Y is linearly dependent on input X values that are not yet known. This is referred to as a linear model.

An equation called the regression equation is calculated from the known input / output sets. Linear regression is predictive in that an new output Y value can be calculated from a new set of X input values, as long as those X values are within the range of Original input X values that were used to calculate the regression equation.

Most often, the "least squares" approach is used to fit the linear regression model. There are other less  frequently-used methods of fitting the regression linear regression such "minimization of lack of fit."

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