Question

Kerri Rafferty​, 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, Rafferty wants to set the delivery fee based on the distance driven to deliver the flowers. Rafferty 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

Requirement 1. Determine the company's cost equation (use the output from the Excel regression). (Round the amounts to two decimal places.) y = $ X + $ Requirement 2. Determine the R-square (use the output from the Excel regression). The R-square is What does Tulip Time's R-square indicate? The R-square indicates that the cost equation explains of the variability in the data. In other words, it Tulip Time feel confident using this cost equation to predict total costs at other volumes within the same relevant range Requirement 3. Predict van operating costs at a volume of 15,000 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? (Round your answer to the nearest cent.) The operating costs at a volume of 15,000 miles is $ Data Table Should the company rely on this cost estimate? Why or why not? Since the r-square is the company Month Miles Driven Van Operating Costs 16,000 $5,490 17,500 $5,700 14,900 January February March April May June 16,200 $4,910 $5,340 $5,820 16,900 15,100 $5,410 July 14,500 $4,920 Print Done

Answer 1

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.87861966
R Square	0.7719725
Adjusted R Square	0.726367
Standard Error	184.004138
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	1	573112.387	573112.387	16.9271802	0.00922537
Residual	5	169287.613	33857.5226
Total	6	742400
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	908.93462	1086.52017	0.83655568	0.4409781	-1884.0544	3701.92362	-1884.0544	3701.92362
X Variable 1	0.28107523	0.06831723	4.11426545	0.00922537	0.10546019	0.45669026	0.10546019	0.45669026
1)
Y = 0.28 X + $908.93
2)
R square	0.7719725
3)
The​ R-square indicates that the cost equation explains 77.19% of the variability in the data. In other​ words, it should be used with caution may or may not feel confident using this cost equation to predict total costs at other volumes within the same relevant range.
4)
Y = 0.28 x 15000 miles  + $908.93	$  5,125.06
5)
Since  r- square is between .50 and .80, the company should use the cost equation with caution.