Question

Please I need help on my last question I have 40min left, I would appreciate

The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table.

Time
Miles
Load
Speed
Oil
7.6
43.0
24.0
45.0
20.0
0.8
98.9
28.0
45.0
28.0
⋮
⋮
⋮
⋮
⋮
5.9
60.7
25.0
53.0
23.0



b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.)

Answer 1

To estimate the regression model for the time until the first engine overhaul using multiple predictors, input the data into statistical software and run a multiple regression analysis to obtain the regression equation and coefficients.

Step-by-step explanation:

To estimate the regression model for forecasting the time until the first engine overhaul based on the given predictor variables (annual miles driven, average load weight, average driving speed, and oil change interval), you would typically use a statistical software package. However, since actual computation details and data are not provided, here is the general process:

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Without the output, it's not possible to provide actual numerical values for the regression model coefficients or to perform additional analysis, such as checking for significance or making predictions.