Need help with Letter "I".

A B C D E F G H SUMMARY OUTPUT H: What is the general form of the regression equation required for this problem? (HINT: N y = bo + bix is the general form of the regression equation for one independent variable) W Regression Statistics 1: Given the information below, what is the regression equation which models monthly 4 Multiple R 0.958310415 heating costs as a function of the four variables below? (this equation should make use 5 R Square 0.918358852 of the values related to letters C, D, E, F, and G below) 6 Adjusted R Square A 0.896587879 J: Why is the Adjusted R Squared value a better measure of goodness of fit than R Squared? 7 Standard Error 34.04777467 For questions K through O, I have given you values of x1, x2, x3, and x4 per the Variables 8 Observations 20 chart below. The value which follows the ..... in each set of parenthesis is the actual 9 heating cost of the home with the characteristics given. For the data given in K through O 10 ANOVA below, choose one set of data and compute the residual. 11 df K: (29, 5, 4, 1900....198) 12 Regression 4 L: (8, 6, 7, 2800...... 355) 13 Residual 15 M: (6, 10, 9, 2500.... 291) 14 Total 19 N: (22, 8, 11, 2000...230) O: (59, 5, 9, 1300...... 42) 15 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 95%ower 95.01 Upper 95.0% 17 Intercept C -29.21827117 97.20142088 -0.3006 0.767849 -236.3981955 177.9617 -236.398 177.9616532 18 X Variable 1 D -1.178281783 0.85630427 -1.37601 0.189017 -3.003451129 0.646888 -3.00345 0.646887563 19 X Variable 2 F -6.89508123 3.55049134 -1.94201 0.071157 -14.46277438 0.672612 -14.4628 0.672611923 20 X Variable 3 F 3.212893373 2.631592842 1.220893 0.240971 -2.396213993 8.822001 -2.39621 8.82200074 21 X Variable 4 G 0.148933656 0.029341618 5.07585 0.000137 0.086393477 0.211474 0.086393 0.211473834 22 Variables: 23 y = average heating cost 24 x1 = temp in winter 25 x2 = amt of insulation 26 *3 = age of furnace 27 x4 = size of house (SF) 28