16.68 11.50 12.03 14.88 13.75 18.11 8.00 7 3 3 4 6 7
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
A soft drink bottler is analyzing the vending machine service routes in his distribution system.
He is interested in predicting the amount of time required by the route driver to service the
vending machines in an outlet. This service activity includes stocking the machine with beverage
products and minor maintenance or housekeeping. The industrial engineer responsible for the
study has suggested that the two most important variables affecting the delivery time (y) are the
number of cases of product stocked (x1) and the distance walked by the route driver (x2). The
collected 25 observations on delivery time are shown in the following table.
He is interested in predicting the amount of time required by the route driver to service the
vending machines in an outlet. This service activity includes stocking the machine with beverage
products and minor maintenance or housekeeping. The industrial engineer responsible for the
study has suggested that the two most important variables affecting the delivery time (y) are the
number of cases of product stocked (x1) and the distance walked by the route driver (x2). The
collected 25 observations on delivery time are shown in the following table.
Use any software to do the calculations like Excel. But please show all the
detailed steps
detailed steps

Transcribed Image Text:(a) With several proper scatter plots check the relationship between the response and the
independent variables
(b) Use matrix notation and find estimator for the regression coefficients
(c) Write the equation of the fitted model based on least squared method
(d) Interpret each estimated regression coefficients
(e) Find an estimator for the total variation of the model.
(f) Test significance of each regression coefficients at level a = 0.05
(g) Find 95% C.I. for each regression coefficients
(h) Test significance of the whole regression model
(i) Find R² and Raj. Comment on the values.

Transcribed Image Text:Observation Number
1
2
3
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Delivery Time,
y (min)
16.68
11.50
12.03
14.88
13.75
18.11
8.00
17.83
79.24
21.50
40.33
21.00
13.50
19.75
24.00
29.00
15.35
19.00
9.50
35.10
17.90
52.32
18.75
19.83
10.75
Number of Cases, x₁
7
3
3
4
6
7
2
7
30
5
16
10
4
6
9
10
6
7
3
17
10
26
9
8
4
Distance, x₂ (ft)
560
220
340
80
150
330
110
210
1460
605
688
215
255
462
448
776
200
132
36
770
140
810
450
635
150
Expert Solution

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VIEWStep 6: g) Testing the significance of the whole regression model
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