The statistics question asks which would be the best method to determine if your data would best be fit with a linear regression model or a quadratic model.
I would think that the residual plot would be the best method. The other 2 choices are the shape of the scatter plot and the correlation coefficient.
I have seen scatter plots that look very liner and have a $.9$ R value, yet when you look at the residual plot you can see a distinctive pattern or curve.
So, isn't the residual plot not only the best but the ONLY method? I guess I'm no longer sure what the R value really does, since R values of .9 can still NOT be a good linear fit.