 Data transformation may be used as a remedial measure to make data suitable for modeling with linear regression if the original data violates one or more assumptions of linear regression.For example, the simplest linear regression models assume a linear relationship between the expected value of "Y" (the response variable to be predicted) and each independent variable (when the other independent variables are held fixed).If linearity fails to hold, even approximately, it is sometimes possible to transform either the independent or dependent variables in the regression model to improve the linearity.