Module 4 HW

# Module 4 HW - 16. A trucking company wants to predict the...

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expense (Y ) for a truck using the number of miles driven during the year (X1) and the age of the truck (X2, in years) at the beginning of the year. The company has gathered the data given in the file P11_16.xlsx. Note that each observation corresponds to a particular truck. model using the given data. these data. P11_16.xlsx. : Yearly Maintenance Expense for Randomly Selected Trucks A. Truck Maintenance Expense Miles Driven Age of Truck SUMMARY OUTPUT 1 \$908.56 10,500 10 2 \$751.12 9,700 7 Regression Statistics 3 \$793.55 9,200 8 Multiple R 0.9643664823 4 \$619.61 8,300 9 R Square 0.9300027122 5 \$380.11 6,500 5 Adjusted R Square 0.9066702829 6 \$368.72 4,500 2 Standard Error 83.46677102 7 \$235.32 3,500 2 Observations 9 8 \$174.93 2,200 3 9 \$256.30 1,800 2 ANOVA df SS MS F Significance F Regression 2 555368.8004989 277684.4002 39.85880344 0.0003429601 Residual 6 41800.21118997 6966.701865 Total 8 597169.0116889 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 12.452670352 61.9174348463 0.201117349 0.8472514689 -139.05383447 163.9591752 -139.05383447 163.95917518 X Variable 1 0.0649539198 0.022926664 2.8331169234 0.0298353619 0.008854394 0.1210534456 0.008854394 0.1210534456 X Variable 2 15.11949319 23.6999822834 0.6379537762 0.5470636766 -42.8722742164 73.1112606 -42.872274216 73.111260603 B. Regression Statistics Multiple R 0.9643664823 R Square 0.9300027122 The standard error of estimate is 83.46677 which is interpreted as accuracy of predictions Adjusted R Square 0.9066702829 made with a regression line. Standard Error 83.46677102 Observations 9 is explained by the regression model. 16. A trucking company wants to predict the yearly maintenance a. Formulate and estimate a multiple regression b. Compute and interpret the standard error of estimate s e and the coefficient of determination R2 for Interpretation for s e and the coefficient of determination R 2 The coefficient of determination, R 2 is 0.93 which is interpreted as 93% of the variation

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for a particular item increases with its age and with the number of bidders. The file P11_18.xlsx contains data
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## This note was uploaded on 02/01/2012 for the course BUSINES BUS-660 taught by Professor Paulshriver during the Spring '11 term at Grand Canyon.

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Module 4 HW - 16. A trucking company wants to predict the...

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