Let the model be: Yi B + BTi + i=1,...,n but suppose you are missing data on the nth observation of r. To deal with the missing data, you do mean imputation, setting Tn = Tn-1 = (n 1)-, then estimating 3 and 3 based on all n observations. (a) Show that, as n, this procedure gives you the same coefficient estimates as simply estimating and 32 from the n-1 observations for which you have complete data. Solution (b) Compare the R-squares from the two regressions. Does goodness-of-fit depend on the approach you take to the missing data?