Transformation of independent variables in polynomial regression models

In representing a relationship between a response and a number of independent variables, it is preferable when possible to work with a simple functional form in transformed variables rather than with a more complicated form in the original variables. In this paper, it is shown that linear transformations applied to independent variables in polynomial regression models affect the t ratio and hence the statistical significance for certain parameters of the polynomial regression models.