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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

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 explanatory 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 until First Engine OverhaulAnnual Miles DrivenAverage Load WeightAverage Driving SpeedOil Change Interval7.742.922.044.016.00.898.320.047.034.06.361.122.062.015.0

For each explanatory variable, discuss whether it is likely to have a positive or negative causal effect on time until the first engine overhaul.

Explanatory variable Effect on time

Annual Miles Driven

Average Load Weight

Average Driving Speed

Oil Change Interval

data

Time Until First Engine Overhaul Annual Miles Driven Average Load Weight Average Driving Speed Oil Change Interval 7.7 42.9 22 44 16 0.8 98.3 20 47 34 8.4 43.7 25 66 13 1.1 110.7 30 62 25 1.4 101.9 32 53 22 2.2 96.8 19 58 19 2.2 93.3 27 52 13 7.8 54.1 24 66 17 8.1 51.4 25 48 14 4.4 84.7 27 51 29 0.7 120.4 32 47 26 5.3 77 22 52 26 5.5 68.8 26 47 24 5.2 55.1 25 61 18 5.8 66.3 16 55 29 8.8 38.9 19 51 20 5.6 52.4 17 54 20 5.7 54.6 24 47 20 4.1 75 26 65 26 6 58.7 22 54 20 6.5 52.5 21 54 22 7 68.3 17 55 17 4.2 94.1 26 59 26 7.3 45.8 19 58 14 6.3 61.1 22 62 15

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