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Linear Regression is a forecasting technique used to predict the value of one variable (called the dependent variable) based upon the value of one or more other variable (the independent variables).
Our example is a simple linear regression model with one independent variable. The data is fit to a linear equation of the form:
Y( i)=CONS+SLOPE*X( i)where Y is the dependent variable, X is the independent variable, CONS is the value of Y when X=0 and SLOPE is the rate of change in Y with a unit change in X.