Regression Analysis captures the relationship between one or more response variables (dependent/predicted variable – denoted by Y) and its predictor variables (independent/explanatory variables – denoted by X) using historical observations of both.

Hence, it estimates the functional relationship between a set of independent variables X1, X2, …, Xp with the response variable Y, which estimate the functional form best fits the historical data.

                             Y = f (X1, X2,.., Xp) + Є

  where Є denotes the “Residual” or unexplained part of Y

 Y = f (X1, X2,.., Xp) + Є

There are various kinds of Regressions based on the nature of: –

•the functional form of the relationship

•the residual

•the dependent variable

•the independent variables

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