How good is this regression Model?

What are the metrics that you would use to answer this question?

Which Independent Variable is the most important predictor variable & why?

Which Independent Variables are not important and why?

How much (percentage) of the variation in the Dependent Variable is accounted for by the Independent Variables in the model? Which value would you use to answer this question?

How much does the monthly rent increase for increase in one Sq. Ft. in premises, keeping everything else constant?

Regression Stopgoes R Square 0.927828975 Adjusted R Square 0.924194463 Standard Error 845.2831017 Observations 147 ANOVA M'S Significance F Regression 182400560.7 4.85768E-76 Residual 139 99315989.57 714503.5221 Total 146 13761 19978 Coolriciants Standard Error Istat P-value Lower 9576 Upper 93% Intercept 25190 92150 9041 38028 -2787173301 0.006081244 -43076.35789 -7323 485204 Rented Soft 0.209058402 0.010727598 27 87747948 8.86251E-59 0.277848032 0.320268771 % Office 1922 329272 859.5535812 2 238427508 0.026910907 222 8389989 3621.819545 Year Bit 6.205948575 4.584375236 1.353717411 0.178023625 -2.858176447 15.2700736 Cir Hit 48.38805005 25.80816359 1.796781993 0.074541676 -4.655324137 97 39142424 TD 280.7750856 76 40493815 3.674829041 0.000338913 129.7089368 431.8412344 GL -140.4947672 72 23526439 -1.944960933 0.053798454 -283.3167296 2 327195116 Lease Date 0.354482196 0.090385688 3.921884132 0.000137489 0.175773619 0.533190774 The resulting regression equation is: Monthly Rent - 25199.92159 + 0.299058402 x SqFt in Premises + 1922 329272 x Percent Office + 6.205948575 x Year Built + 46.36805005 x Feet of Clear Height + 280.7750856 x Number of Truck-High Doors 140.4947672 x Number of Ground Level Doors + 0.354482196 x Date of Lease