## Polynomial Regression in R

If you find yourself trying to do a polynomial regression in R, you may find Polynomial Regression in R by Bret Larget extremely helpful. I always have a hard time remembering the `I(x^2)` syntax. The explanations of the underlying statistics are also useful if you already know a little bit of what’s going on.

While r

^{2}has this nice interpretation, its major deficiency is that it will always increase as you add additional variables — the residual sum of squares from a small model must be at least as large as that from a larger model of which it is a special case. So, looking at r^{2}is not a good strategy for picking out a good model, because you can get increasingly better r^{2}values by addiing spurious variables. One attempt to correct for this is to compute the adjusted r^{2}statistic.