Module 4 of Statistics and Probability

Module 4 of Statistics and Probability - the model assumes...

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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. P11_16.xlsx. : Yearly Maintenance Expense for Randomly Selected Trucks SUMMARY OUTPUT Truck Maintenance_Expense Miles_Driven Age_of_Truck 1 $908.56 10,500 10 Regression Statistics 2 $751.12 9,700 7 Multiple R 0.964366 3 $793.55 9,200 8 R Square 0.930003 4 $619.61 8,300 9 Adjusted R Square 0.90667 5 $380.11 6,500 5 Standard Error 83.46677 6 $368.72 4,500 2 Observations 9 7 $235.32 3,500 2 8 $174.93 2,200 3 ANOVA 9 $256.30 1,800 2 df SS MS F ignificance F Regression 2 555368.8 277684.4 39.8588 0.000343 Residual 6 41800.21 6966.702 Total 8 597169 the model results are summarisd in the table above.
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Unformatted text preview: the model assumes that maintenance expenses depend on miles driven and the age of the truck. Coefficientstandard Err t Stat P-value Lower 95%Upper 95%Lower 95.0% Upper 95.0% Intercept 12.45267 61.91743 0.201117 0.847251 -139.0538 163.9592 -139.0538 163.9592 Y = 12.45267 +.064954*miles + 15.11949 *age X Variable 1 0.064954 0.022927 2.833117 0.029835 0.008854 0.121053 0.008854 0.121053 the results show a high value of explanatory power (93%) X Variable 2 15.11949 23.69998 0.637954 0.547064 -42.87227 73.11126 -42.87227 73.11126 age is a significant variable (t<2), whereas miles are not statistically significant ( t value >2) 16. A trucking company wants to predict the yearly maintenance a. Formulate and estimate a multiple regression...
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