Big Time Corporation wanted to determine the relationship between its monthly operating costs and a potential...

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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 0.991108748 R Square 0.982296551 Adjusted R Square 0.977870689 Standard Error 67.58593536 Observations 6 ANOVA df Regression 1 SS 1013811.899 1013811.899 221.9446735 MS F Significance F 0.00011823 Residual 4 18271.43463 4567.858659 Total 5 1032083.333 Coefficients Standard Error Intercept X Variable 1 2945.94652 0.718590832 194.105844 Stat 15.17701095 P-value 0.000109885 0.04823467 14.89780767 Lower 95% 2407.022299 0.584669919 What is closest to the total cost if the firm uses 4,200 machine hours? 0.00011823 A. $12,372,975.38 B. $2,945.95 C. $5,964.03 D. $3,018.08 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 0.991108748 R Square 0.982296551 Adjusted R Square 0.977870689 Standard Error 67.58593536 Observations 6 ANOVA df Regression 1 SS 1013811.899 1013811.899 221.9446735 MS F Significance F 0.00011823 Residual 4 18271.43463 4567.858659 Total 5 1032083.333 Coefficients Standard Error Intercept X Variable 1 2945.94652 0.718590832 194.105844 Stat 15.17701095 P-value 0.000109885 0.04823467 14.89780767 Lower 95% 2407.022299 0.584669919 What is closest to the total cost if the firm uses 4,200 machine hours? 0.00011823 A. $12,372,975.38 B. $2,945.95 C. $5,964.03 D. $3,018.08