A firm wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis performed using Microsoft Excel showed the following information: (Click the icon to view the regression data.) 1. Given this output, write the firm's monthly cost equation. 2. Should management use this equation to predict monthly operating costs? Explain your answer. 1. Given this output, write the firm's monthly cost equation. (Round your answers to two decimal places, X.XX.) The firm's month cost equation is: y = [* +- 2. Should management use this equation to predict monthly operating costs? Explain your answer. This equation to predict costs. The R-square statistic can range from a high of| to a low of . In this case, the R-square indicates that the cost equation , indicating there relationship between the potential cost driver and the firm's operating costs - X Regression data Regression Statistics Multiple R 0.87 R Square 0.86 Adjusted R Square 0.84 Standard Error 398.49 Observations 12 ANOVA df SS MS F Significance F Regression 1 2365870.5 2365871 14.89886 0.0032 Residual 10 1587954.5 158795 Total 11 3953825 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 9942.83 406.44 24.46 0.00 9037.23 10848.43 X Variable 1 0.92 0.23 3.86 0.00 0.37 1.40 Print Done