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Data Table SUMMARY OUTPUT Regression Statistics Multiple R 0.991108748 R Square 0.982296551 Adjusted R Square 0.977870689 Standard Error 67.58593536 Observations ANOVA df Significance F .
Data Table SUMMARY OUTPUT Regression Statistics Multiple R 0.991108748 R Square 0.982296551 Adjusted R Square 0.977870689 Standard Error 67.58593536 Observations ANOVA df Significance F . 0.00011823 Regression Residual Total SS F 1013811.8991013811.899 221.9446735 18271.43463 4567.858659 1032083.333 1 4 5 Intercept X Variable 1 Coefficients 2945.94652 .718590832 Standard Error t Stat 1 94.105844 15.17701095 0.04823467 14.89780767 P-value 0.000109885 0.00011823 Lower 95% 2 407.022299 0.584669919 0 Print [ Done] Print Done Valle Crucis 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) (Click the icon to view the portion of the regression analysis.) What is closest to the total cost if the firm uses 6,000 machine hours? O A. $14,729,732.60 OB. $7,257.49 OC. $6,538.90 OD. $1,365.59
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