Consider the delivery time data discussed in Example 11.3 . a. Develop a regression model using the prediction data set. b. How do the estimates of the parameters in this model compare with those from the model developed from the estimation data? What does this imply about model validity? c. Use the model developed in part a to predict the delivery times for the observations in the original estimation data. Are your results consistent with those obtained in Example 11.3 ?
Consider the delivery time data discussed in Example 11.3 . a. Develop a regression model using the prediction data set. b. How do the estimates of the parameters in this model compare with those from the model developed from the estimation data? What does this imply about model validity? c. Use the model developed in part a to predict the delivery times for the observations in the original estimation data. Are your results consistent with those obtained in Example 11.3 ?
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
Consider the delivery time data discussed in Example 11.3 .
a. Develop a regression model using the prediction data set.
b. How do the estimates of the parameters in this model compare with those
from the model developed from the estimation data? What does this
imply about model validity?
c. Use the model developed in part a to predict the delivery times for the
observations in the original estimation data. Are your results consistent
with those obtained in Example 11.3 ?
Transcribed Image Text:TABLE 11.3 Delivery Time Data
Observation,
Cases,
Distance,
Delivery Time,
Estimation (E) or
i
Prediction (P) Data Set
1
7
560
16.68
3
220
11.50
3
3
340
12.03
4
4
80
14.88
E
5
6.
150
13.75
6
7
330
18.11
E
110
8.00
7
210
17.83
E
9.
30
1460
79.24
E
10
605
21.50
E
11
16
688
40.33
12
10
215
21.00
13
4
255
13.50
19.75
14
462
P.
15
9.
448
24.00
16
10
776
29.00
17
6
200
15.35
19.00
18
7
132
E
19
3
36
9.50
20
17
770
35.10
E
21
10
140
17.90
22
26
810
52.32
E
23
450
18.75
19.83
E
24
8
635
E
25
4
150
10.75
E
26
22
905
51.00
27
7
520
16.80
E
28
15
290
26.16
P.
29
500
19.90
30
6.
1000
225
24.00
31
6.
18.55
E
32
10
775
31.93
33
4
212
16.95
34
144
7.00
35
3
126
14.00
36
12
655
37.03
37
10
420
18.62
38
7
150
16.10
39
8.
360
24.38
40
32
1530
64.75
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