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