Kelly Battle, owner of Rose Red, operates a local chain of floral shops. Each shop has its own delivery van. Instead of charging a flat delivery fee, Battle wants to set the delivery fee based on the distance driven to deliver the flowers. Battle 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. She has the following data from the past seven months: E (Click the icon to view the data.) Data Table Read the requirements. Requirement 1. Determine the company's cost equation (use the output from the Excel regression). (Round the amounts to two decimal places.) Month Miles Driven Van Operating Costs y = $ 27 X + $ 947.20 January 16,400 $5,480 February. 17,500 $5,400 Requirement 2. Determine the R-square (use the output from the Excel regression). March 15,000 $4,950 The R-square is 0.847169 April 16,100 $5,270 What does Rose Red's R-square indicate? May 17,300 $5,740 June 15,600 $5,440 The R-square indicates that the cost equation explains 84.7% of the variability in the data. In other words, it does not fit the data at all. Rose Red should feel confident us July. 14,500 $4,680 range. Requirement 3. Predict van operating costs at a volume of 16,000 miles assuming the company would use the cost equation from the Excel regression regardless of its R-square. Should nearest cent.) Print Done The operating costs at a volume of 16,000 miles is $ 5267.20 Should the company rely on this cost estimate? Why or why not? Since the r-square is over .80 the company should use the cost equation with caution.