A company that offers cars for rent wants to better understand costs. When cars are returned, they are thoroughly cleaned before being rented again. The manager believes that the variable portion of the cleaning costs relates to the number of rental returns. She has gathered the following data: Month Rental Returns Cleaning Costs January 2,500 $ 12,000 February 2,500 $ 13,600 March 2,800 $ 12,800 April 3,200 $ 15,800 May 3,700 $ 17,200 June 5,200 $ 25,300 July 5,600 $ 23,200 August 5,700 $ 24,700 September 4,800 $ 23,800 October 4,700 $ 24,100 November 2,300 $ 11,700 December 3,200 $ 17,700 Using least-squares regression, estimate the variable cost per rental return and the monthly fixed cost incurred to clean cars. What is the R2 rounded to the nearest whole percentage? (Round Fixed cost to the nearest whole dollar amount and the Variable cost per unit to 2 decimal places. Enter the % in whole numbers (i.e. .67 = 67))
Fixed Cost = $2822
Variable Cost per unit = $4.07 per unit
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.962677 | |||||||
R Square | 0.926748 | |||||||
Adjusted R Square | 0.919423 | |||||||
Standard Error | 1533.017 | |||||||
Observations | 12 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 2.97E+08 | 2.97E+08 | 126.5148 | 5.36E-07 | |||
Residual | 10 | 23501422 | 2350142 | |||||
Total | 11 | 3.21E+08 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 2822.488 | 1461.681 | 1.930987 | 0.0823 | -434.341 | 6079.318 | -434.341 | 6079.318 |
X Variable 1 | 4.069916 | 0.361839 | 11.24788 | 5.36E-07 | 3.26369 | 4.876143 | 3.26369 | 4.876143 |
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