Conveniently, these models are all linear from the point of view of estimation, since the regression function is linear in terms of the unknown parameters a0, a1, .... Therefore, for least squares analysis, the computational and inferential problems of polynomial regression can be completely addressed using the techniques of multiple regression. This is done by treating x, x2, ... as being distinct independent variables in a multiple regression model.

http://en.wikipedia.org/wiki/Polynomial_regression