The Company wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis showed the following information (note: only a portion of the regression analysis results is presented here): SUMMARY OUTPUT Regression Statistics Multiple R 0.001108748 R Square 0.982296551 Adjusted R Square 0.977870680 Standard Error 67.58593536 Observations ANOVA Significance F 0.00011823 Regression Residual Total SS MS F 1013811.8991013811.899 221.9446735 18271.43483 4567 858050 1032083,333 1 4 5 Lower 95% 2407022200 0584600919 Coefficients Standard Error Star P.value Intercept 2945.94652 194.105844 15.17701095 0.000109885 X Variage 1 0.718590832 0.04823467 14 89780767 0.00011823 What is closest to the total cost if the firm uses 4,200 machine hours? $12,372,975.38 $2,945.95 $3,018.08 O $5,064.03