Big Time Corporation 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 0991108748 R Square 0.982296551 Adjusted R Square 0.977870689 Standard Emor 87.58503536 Observations ANOVA 55 Regression 1 Residual 4 Total MS 1013611.000 1013011.800 221.0440735 18271.43463 4567.858659 1032063 333 Coefficients Standard Error Intercept 2045 04652 XVariable 1 0718590832 Stet Preve 104 105844 15.17701005 0.000109685 004823467 14 80780767 000011823 What is closest to the total cost if the firm uses 6,000 machine hours? OA $1,365.59 On $7,257 49 OC. $6.538.00 OD. $14,729,732.60 Significance F 0.00011823 Lower 95% 2407022290 0554669910