Question 6: 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 travelled (kilometres) and x2 = the number of deliveries made. Suppose that the model equation is Y = -0.950+ 0.055x1 +0.901x2 + € (a) (b) How would you interpret ₁ = 0.055, the coefficient of the predictor x₁? What is the interpretation of 32 = 0.901? (c) If o = 0.9 hour, what is the probability that travel time will exceed 5.5 hours when four deliveries are made and the distance travelled in 80 km. (d) If o = 0.9 hour, what is the probability that travel time will be between 5.5 and 6.5 hours when four deliveries are made and the distance travelled in 80 km.
Question 6: 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 travelled (kilometres) and x2 = the number of deliveries made. Suppose that the model equation is Y = -0.950+ 0.055x1 +0.901x2 + € (a) (b) How would you interpret ₁ = 0.055, the coefficient of the predictor x₁? What is the interpretation of 32 = 0.901? (c) If o = 0.9 hour, what is the probability that travel time will exceed 5.5 hours when four deliveries are made and the distance travelled in 80 km. (d) If o = 0.9 hour, what is the probability that travel time will be between 5.5 and 6.5 hours when four deliveries are made and the distance travelled in 80 km.
Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.3: Modeling Data With Power Functions
Problem 3TU
Related questions
Question
![Question 6: 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 travelled (kilometres) and x₂ = the number of
deliveries made. Suppose that the model equation is
Y = -0.950+ 0.055x1 +0.901x2 + €
(a)
(b)
How would you interpret 3₁
32 = 0.901?
=
=
0.055, the coefficient of the predictor x₁? What is the interpretation of
(c)
If o = 0.9 hour, what is the probability that travel time will exceed 5.5 hours when four deliveries are made
and the distance travelled in 80 km.
(d)
If o = 0.9 hour, what is the probability that travel time will be between 5.5 and 6.5 hours when four deliveries
are made and the distance travelled in 80 km.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F67540c0c-0996-4e08-9c56-e8b7c18daa2d%2Fbea53e20-c580-4ca7-821f-a93a68577f74%2Fr2wxr5_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Question 6: 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 travelled (kilometres) and x₂ = the number of
deliveries made. Suppose that the model equation is
Y = -0.950+ 0.055x1 +0.901x2 + €
(a)
(b)
How would you interpret 3₁
32 = 0.901?
=
=
0.055, the coefficient of the predictor x₁? What is the interpretation of
(c)
If o = 0.9 hour, what is the probability that travel time will exceed 5.5 hours when four deliveries are made
and the distance travelled in 80 km.
(d)
If o = 0.9 hour, what is the probability that travel time will be between 5.5 and 6.5 hours when four deliveries
are made and the distance travelled in 80 km.
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