With regard to Josh Tabor's question, the TI treats only nonlinear models that can be linearized by an appropriate transformation. The r and R^2 terms are calculated (I think) from the linearized version of the data. When the results are transformed back to the original scale, the r and R^2 are inappropriate measures. In my opinion, they should not be given.
It should be pointed out to students that fitting a least squares line to the transformed data is not the same as fitting a nonlinear model directly by least squares.