Kathy Jungemann, 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, Jungemann wants to set the delivery fee based on the distance driven to deliver the flowers. Jungemann 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: Regression analysis 1 SUMMARY OUTPUT Regression Statistics 3 Multiple R 0.87 4 R Square 0.75 5 Adjusted R Square 0.71 6 Standard Error 153.46 13 7 Observations 8 ANOVA 9 10 Regression 11 Residual 12 Total 23 df SS MS F Significance F 1 362,391.24 362,391.24 15.39 0.0112 5 117,751.61 23,550.32 6 480,142.86 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 14 Intercept 1,784,73 884.55 2.02 0.10 -489.09 4,058.55 15 X Variable 1 0.22 0.06 3.92 0.01 0.07 0.36 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 Tulip Time's R-squared indicate? 3. Predict van operating costs at a volume of 17,000 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? Print Done - X Si