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Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Question
![Consider the table below which represents the number of active credit card accounts issued by a small credit
union in a particular customer segment from 1994 to 2017 and a relevant forecast method.
Time
Credit cards
A
B
abs
sq
abs%
err
1994
13260
13260
60
1995
13310
13319
60
10
10
97
0.0007
1996
13383
13379
60
13379
4
4
20
0.0003
1997
13427
13438
59
13439
12
12
149
0.0009
1998
13455
13493
58
13497
42
42
1743
0.0031
1999
13520
13548
57
13551
31
31
962
0.0023
2000
13663
13611
59
13605
-58
58
3360
0.0042
2001
13717
13675
60
13670
47
47
2220
0.0034
2002
13753
13737
61
13735
-17
17
296
0.0013
2003
13792
13798
61
13798
6
6
37
0.0004
2004
13858
13858
61
13858
1
1
0.0000
2005
13915
13919
61
13919
4
4
13
0.0003
2006
13966
13978
60
13979
13
13
177
0.0010
2007
14017
14036
60
14038
21
21
450
0.0015
2008
13945
14081
55
14096
151
151
22852
0.0108
2009
14008
14123
51
14136
128
128
16382
0.0091
2010
14076
14164
48
14174
98
98
9658
0.0070
2011
14122
14204
46
14213
90
90
8128
0.0064
2012
14164
14241
43
14249
85
85
T303
0.0060
2013
14194
14275
40
14284
90
90
8052
0.0063
2014
14238
14307
38
14315
77
77
5971
0.0054
2015
14310
14342
37
14345
35
35
1210
0.0024
2016
14339
14375
36
14379
40
40
1606
0.0028
2017
14340
14403
34
14411
70
70
4943
0.0049
2018
14437
МАЕ
MSE
МАРЕ
49
4158
RMSE
D
Based on the information provided in the table, which of the following statements is correct?
[Press CTRL and "-" to see the whole table by reducing the font size. Press CTRL and "+" to restore the
font size]
Select one:
a. The model provided is not a suitable forecast method for the data as it doesn't capture seasonal
components of the time series
b. The model provided is a suitable forecast model for the time series without any changes required
c. This model has an adjustable smoothing parameter for level as it is an ARRSES model
d. The model theoretically captures the systematic components of the time series but can likely be improved
by changing the two relevant smoothing parameters
O e. The model assumes a constant trend for the time series](https://content.bartleby.com/qna-images/question/b4556a07-42d5-4f6c-848a-6a301a20ce83/fc913757-c9b5-4e29-bb11-851518ef44db/lgho2sq_thumbnail.png)
Transcribed Image Text:Consider the table below which represents the number of active credit card accounts issued by a small credit
union in a particular customer segment from 1994 to 2017 and a relevant forecast method.
Time
Credit cards
A
B
abs
sq
abs%
err
1994
13260
13260
60
1995
13310
13319
60
10
10
97
0.0007
1996
13383
13379
60
13379
4
4
20
0.0003
1997
13427
13438
59
13439
12
12
149
0.0009
1998
13455
13493
58
13497
42
42
1743
0.0031
1999
13520
13548
57
13551
31
31
962
0.0023
2000
13663
13611
59
13605
-58
58
3360
0.0042
2001
13717
13675
60
13670
47
47
2220
0.0034
2002
13753
13737
61
13735
-17
17
296
0.0013
2003
13792
13798
61
13798
6
6
37
0.0004
2004
13858
13858
61
13858
1
1
0.0000
2005
13915
13919
61
13919
4
4
13
0.0003
2006
13966
13978
60
13979
13
13
177
0.0010
2007
14017
14036
60
14038
21
21
450
0.0015
2008
13945
14081
55
14096
151
151
22852
0.0108
2009
14008
14123
51
14136
128
128
16382
0.0091
2010
14076
14164
48
14174
98
98
9658
0.0070
2011
14122
14204
46
14213
90
90
8128
0.0064
2012
14164
14241
43
14249
85
85
T303
0.0060
2013
14194
14275
40
14284
90
90
8052
0.0063
2014
14238
14307
38
14315
77
77
5971
0.0054
2015
14310
14342
37
14345
35
35
1210
0.0024
2016
14339
14375
36
14379
40
40
1606
0.0028
2017
14340
14403
34
14411
70
70
4943
0.0049
2018
14437
МАЕ
MSE
МАРЕ
49
4158
RMSE
D
Based on the information provided in the table, which of the following statements is correct?
[Press CTRL and "-" to see the whole table by reducing the font size. Press CTRL and "+" to restore the
font size]
Select one:
a. The model provided is not a suitable forecast method for the data as it doesn't capture seasonal
components of the time series
b. The model provided is a suitable forecast model for the time series without any changes required
c. This model has an adjustable smoothing parameter for level as it is an ARRSES model
d. The model theoretically captures the systematic components of the time series but can likely be improved
by changing the two relevant smoothing parameters
O e. The model assumes a constant trend for the time series
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