Consider Example 12.4. Figure 12.1 on page 479 displays a SAS printout of an analysis of the model containing variables x , x , and x . Focus on the confidence interval of the mean response μ at the (x , x , x ) locations representing the 13 data points. Consider an item in the printout indicated by C.V. This is the coefficient of variation, which is defined by where is the root mean squared error. The coefficient of variation is often used as yet another criterion for comparing competing models. It is a scale-free quantity which expresses the estimate of σ, namely s, as a percent of the average response

. In competition for the “best” among a group of competing models, one strives for the model with a small value of C.V. Do a regression analysis of the data set shown in Example 12.4 but eliminate x . Compare the full (x , x , x ) model with the restricted (x , x ) model and focus on two criteria: (i) C.V.; (ii) the widths of the confidence intervals on μ . For the second criterion you may want to use the average width. Comment.