A trucking company considered a multiple regression model for relating the depen

Question

A trucking company considered a multiple regression model for relating the dependent variable of total daily travel time for one of its drivers (hours) to the predictors distance traveled (miles) and the number of deliveries of made. After taking a random sample, a multiple regression was performed and the equation is (time) = 0.02*(distance) + 0.657*(deliveries) - 1.463. Suppose for a given driver's day, he is scheduled to drive 131.131 miles and make 6.936 stops. Suppose it took him 17.633 hours to complete the trip. What is the residual based on the regression model?

Question 10 options:

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1) -125.4144 2) -11.9164 3) -10.4534 4) 11.9164 5) We do not know the observations in the data set, so we cannot answer that question.

Explanation / Answer

Correct Answer : Option    (4)    11.9164

Since

The estimated time is

Time = 0.02*(distance) + 0.657*(deliveries) - 1.463

         = 0.02*(131.131) + 0.657*(6.936) - 1.463

         =5.716572

The actual time is taken 17.633 hours

The residual error is 17.633 - 5.716572 = 11.91643

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