B I Uvabxx APAv Normal No Spacing Heading 1 Heading 2 Subtitle Styles Pane SUMMARY OUTPUT Regression Statistics Multiple R 0.99402946 R Square 0.98809456 Adjusted R Sq 0.98743315 Standard Erro 3.32152584 Observations 115 ANOVA df SS MS F Significance F Regression 6 98889.9602 16481.66 1493.91429 1.852E-101 Residual 108 1191.51366 11.0325339 Total 114 100081.474 Coefficients Standard Error t Stat P-value Lower 95%% Upper 95% Lower 95.0% Upper 95.0% Intercept -7.608176 3.05575054 -2.4897896 0.0143062 -13.665204 -1.5511483 -13.665204 -1.5511483 rconpc 1.22906766 0.04514818 27.2229709 3.58576-50 1.13957613 1.31855919 1.13957613 1.31855919 -17.026311 10.4167551 -1.634512 0.10506302 -37.674126 3.62150494 -37.674126 3.62150494 exports -6.409E-06 3.7198E-05 -0.172307 0.86351863 -8.014E-05 6.7323E-05 8.014E-05 6.7323E-05 debtgap 3.55392523 2.66613298 1.33298874 0.18534066 -1.7308129 8.83866332 -1.7308129 8.83866332 expenditure 1.7413E-05 2.5079E-05 0.69434832 0.48895475 -3.23E-05 6.7123E-05 -3.23E-05 6.7123E-05 hpnom -0.0351139 0.02364014 -1.4853522 0.14036369 -0.0819728 0.01174492 -0.0819728 0.01174492 (f) Which regression, the one in (a) or the one in (e), is a better fit for the data? Please explain