The credit rating data from Exercise 12.27 were reanalyzed, using only the monthly in-come variable as a predictor. JMP results are shown.
a. By how much has the regression sum of squares been reduced by eliminating age and debt percentage as predictors?
b. Do these variables add statistically significant (at normal a levels) predictive value, once income is given?

In exercise
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Responss1 Rat ing acors Supary of e1t Square RSquare ad1 Root Mean Square Brror 571792 Mean of Response Coservations for Sun Mgts) 00 0.895261 o. g 95 051 65.044 Parsneter Estlmates Term Intercept Monthly incoe 0.0135544 .000208 65.24 0.0000 Estinate std grror t Ratio Prob 30.152827 0.572537 52.67 0.0000 Reaponse Rating scare summary of Pit RSquare a] Root Hean Square Rror 2.023398 Hean or Response Cbservations cr Sum Wgts) 0979443 65:044 Farameter Estisazes Datimate std ErrOr t Ratio Probatt 54.657197 0.634731 86.10 0.0000 Intercept 0 011586 0.48 .6285 xonthly income Ο.0100597 0.000157 64.13 0.0000 239 0,883684 45.21 .0000 Debt traction 9.95 Eitect Test Npam DF Sum or Squares Ratto PP 0.960 0.2344 0.6285 16835.19S 4112.023 0.0000 8363.627 2044.05 0.0000 ource Nentnly incone Debt frastion 1 hale-Modal Test 100 40 30 40 50 0 70 90 90 100 Rating score Predicted analyeis of variance DF Sum of squars 97349 239 2030.63 99379,032 Squara Ratia 22449.4 7925.929 Model 496 4 Prob C Total 49 0.0000