0 Regression analysis Regression Statistics Multiple R 0.86 R Square 0.75 Adjusted R Square 0.70 Standard Error 171.55 Observations 7 ANOVA of SS Significance F 0 .0120 Regression 1 M SF 435,336.22 29,429.90 435,336.22 147,149.49 14.79 Residual 6 582,485.71 Total Coefficients 709.81 0.29 Standard Error t 1,150.73 0.07 Stat 0.62 3.85 Lower P-value 95% 0.56 -2,248.24 0.010.09 Intercept X Variable 1 Upper 95% 3,667.85 0.48 Print Done E6-28A (similar to) Question Help Kim Meyer, owner of Tulip Time, operates a local chain of floral shops. Each shop has its own delivery van. Instead of charging a flat delivery fee, Meyer wants to set the delivery fee based on the distance driven to deliver the flowers. Meyer 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. Tulip Time 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.) Requirements 1. Determine the firm's cost equation (use the output from the Excel regression). 2. Determine the R-square (use the output from the Excel regression). What does Tulip Time's R-square 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-square. Should the company rely on this cost estimate? Why or why not? Requirement 1. Determine the firm's cost equation (use the output from the Excel regression). (Enter amounts to two decimal places.) y=$ O x +$D