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

ID: 3045904 • Letter: A

Question

A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors X1 = distance traveled (miles) and x2the number of deliveries made. Suppose that the model equation is =-0.800 0.060x1 + 0.900x2 (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret 0.060, the coefficient of the predictor x? The total daily travel time increases by 0.060 hours when the distance traveled increases by 1 When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours The average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours What is the interpretation of 2 = 0.900? When the distance traveled is held fixed, the average change in travel time associated with one extra delivery is 0.900 hours When the distance traveled is constant, the change in travel time associated with one delivery is 0.900 hours. The total daily travel time increases by 0.900 hours with one extra delivery. The average change in travel time associated with one extra delivery is 0.900 hours. c) If ·0.5 hour, what is the probability that travel time will be at most 6 hours places.) t en our deliveries are made and the distance rave e s 50 miles? Round your answer four de imal

Explanation / Answer

a) mean value of travel time =-0.8+0.06*50+0.9*4 =5.8

b)

2nd option is correct

1st option is correct

c)

her eexpected mean =-0.8+0.06*50+0.9*4=5.8

hence probability =P(X<6) =P(Z<(6-5.8)/0.5)=P(Z<0.4)=0.6554

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