A student used multiple regression analysis to study how Y is influenced by Xl and X2. The following results were obtained. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept 0.7892705 8 0.6229480 5 0.6174835 3 27.358743 2 141 2 138 140 Coefficients 296.64498 9 -6.4509072 -28.844368 ss 170656.176 103293.1148 273949.2908 Standard Error 17.72760793 1.877056182 1.943882236 MS 85328.088 748.5008318 t Stat 16.7335035 -3.436715017 -14.83853699 113.9986549 p-value 5.08711E-35 0.000778428 2.25649E-30 Significance F 5.91129E-30 Lower 95% 261.5921273 -10.162417 -32.68801371 upper 95% 331.6978512 -2.739397331 -25.00072325