Kim Woo, owner of Rose Ready, operates a local chain of floral shops. Each shop has its own delivery van. Instead of charging a flat delivery fee, Woo wants to set the delivery fee based on the distance driven to deliver the flowers. Woo wants to separate the fixed and variable portions of her van operating costs so that she has a better idea how delivery distance affects these costs. Rose Ready does a regression analysis on the next year's data using Excel. The output generated by Excel is as follows: (Click the icon to view the regression analysis.) Read the requirements Requirement 1. Determine the firm's cost equation (use the output from the Excel regression). (Enter amounts to two decimal places.) y= Regression analysis 1 SUMMARY OUTPUT 2 Regression Statistics 3 Multiple R 0.83 4 R Square 0.69 5 Adjusted R Square 0.63 6 Standard Error 127.8 7 Observations 8 ANOVA 9 10 Regression df SS MS F Significance F 1 185,536.45 185,536.45 11.36 0.0199 11 Residual 12 Total 5 81,663.55 16,332.71 6 267,200.00 13 Coefficients Standard Error t Stat P-value 14 Intercept 2,532.42 813.67 3.11 0.03 Lower 95% 440.81 Upper 95% 4,624.0 15 X Variable 1 0.17 0.05 3.37 0.02 0.04 0.3 Requirements 1. Determine the firm's cost equation (use the output from the Excel regression). 2. Determine the R-squared (use the output from the Excel regression). What does Rose Ready's R-squared indicate? 3. Predict van operating costs at a volume of 16,500 miles assuming the company would use the cost equation from the Excel regression regardless of its R-squared. Should the company rely on this cost estimate? Why or why not