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) = 0.03*(distance) + 1.02*(deliveries) - 1.305. Suppose for a given driver's day, he is scheduled to drive 206.609 miles and make 13.27 stops. Suppose it took him 10.862 hours to complete the trip yielding a residual of 7.567. What is the best interpretation of this residual?

a) The number of hours taken is 7.567 hours larger than what we would expect.

b. The number of hours taken is 10.862 hours larger than what we would expect.

c. The number of deliveries is 7.567 less than what we would expect.

d. The number of hours taken is 7.567 hours less than what we would expect.

e. The number of deliveries is 7.567 larger than what we would expect.