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GETFILE='C:\Users\Dell\Downloads\Cell_Inter.sav'.
DATASET NAME DataSet1 WINDOW=FRONT.QUICK CLUSTERfunused0 funused1 funused2 funused3 funused4 funused5 funused6 funused7funused8 funused9/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(10) CONVERGE(0)/METHOD=KMEANS(NOUPDATE)/PRINT INITIAL.
Initial Cluster Centers
Cluster
1 2 3
SMS 1 1 2
Alarm1 1 2
Camera 1 2 1
Scheduler 1 2 2
Music / Radio Playback 1 2 2
Games 1 2 2
Internet 1 2 1
Time and Date 1 2 2
Download 1 2 1
Other 2 2 1
Iteration History(a)
IterationChange in Cluster Centers
1 2 3
1 .906 1.112 .800
2 .028 .081 .552
3 .023 .062 .247
4 .000 .041 .225
5 .000 .093 .340
6 .046 .044 .220
7 .097 .022 .273
8 .030 .040 .086
9 .075 .036 .155
10.021 .019 .060
a Iterations stopped because the maximum number of iterations was performed. Iterations failed to converge. Themaximum absolute coordinate change for any center is .034. The current iteration is 10. The minimum distancebetween initial centers is 2.449.
Final Cluster Centers
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Cluster
1 2 3
SMS 1 1 1
Alarm 1 1 2
Camera 2 2 1
Scheduler 1 2 2
Music / Radio Playback 1 2 2
Games 1 1 1
Internet 2 2 2
Time and Date 1 1 2
Download 1 2 1
Other 2 2 2
Number of Cases in each Cluster
Cluster 1 86.000
2 73.000
3 47.000
Valid 206.000
Missing .000
QUICK CLUSTERfunused0 funused1 funused2 funused3 funused4 funused5 funused6 funused7funused8 funused9/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(20) CONVERGE(0)/METHOD=KMEANS(NOUPDATE)
/PRINT INITIAL.
Quick Cluster
Initial Cluster Centers
Cluster
1 2 3
SMS 1 1 2
Alarm 1 1 2
Camera 1 2 1
Scheduler 1 2 2Music / Radio Playback 1 2 2
Games 1 2 2
Internet 1 2 1
Time and Date 1 2 2
Download 1 2 1
Other 2 2 1
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Iteration History(a)
Iteration
Change in Cluster Centers
1 2 3
1 .906 1.112 .800
2 .028 .081 .552
3 .023 .062 .2474 .000 .041 .225
5 .000 .093 .340
6 .046 .044 .220
7 .097 .022 .273
8 .030 .040 .086
9 .075 .036 .155
10 .021 .019 .060
11 .000 .000 .000
a Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change forany center is .000. The current iteration is 11. The minimum distance between initial centers is 2.449.
Final Cluster Centers
Cluster
1 2 3
SMS 1 1 1
Alarm 1 1 2
Camera 2 2 1
Scheduler 1 2 2
Music / Radio Playback 1 2 2
Games 1 1 1
Internet 2 2 2
Time and Date 1 1 2
Download 1 2 1
Other 2 2 2
Number of Cases in each Cluster
Cluster 1 86.000
2 73.000
3 47.000
Valid 206.000
Missing .000
QUICK CLUSTERfunused0 funused1 funused2 funused3 funused4 funused5 funused6 funused7funused8 funused9/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(20) CONVERGE(0)/METHOD=KMEANS(NOUPDATE)/SAVE CLUSTER/PRINT INITIAL.
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Initial Cluster Centers
Cluster
1 2 3
SMS 1 1 2
Alarm 1 1 2
Camera 1 2 1
Scheduler 1 2 2
Music / Radio Playback 1 2 2
Games 1 2 2
Internet 1 2 1
Time and Date 1 2 2
Download 1 2 1
Other 2 2 1
Iteration History(a)
Iteration
Change in Cluster Centers
1 2 3
1 .906 1.112 .800
2 .028 .081 .552
3 .023 .062 .247
4 .000 .041 .225
5 .000 .093 .340
6 .046 .044 .220
7 .097 .022 .273
8 .030 .040 .086
9 .075 .036 .155
10 .021 .019 .060
11 .000 .000 .000
a Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change forany center is .000. The current iteration is 11. The minimum distance between initial centers is 2.449.
Final Cluster Centers
Cluster
1 2 3
SMS 1 1 1
Alarm 1 1 2
Camera 2 2 1
Scheduler 1 2 2Music / Radio Playback 1 2 2
Games 1 1 1
Internet 2 2 2
Time and Date 1 1 2
Download 1 2 1
Other 2 2 2
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Number of Cases in each Cluster
Cluster 1 86.000
2 73.000
3 47.000
Valid 206.000
Missing .000
USE ALL.COMPUTE filter_$=(QCL_1 = 3).VARIABLE LABEL filter_$ 'QCL_1 = 3 (FILTER)'.VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.FORMAT filter_$ (f1.0).FILTER BY filter_$.EXECUTE .FREQUENCIESVARIABLES=gender educatn service contype chrgfreq paymode/ORDER= ANALYSIS .
Frequencies
Statistics
Gender of
respondentLevel of
education
Name ofcurrentserviceprovider
ConnectionType
MonthlyRechargefrequency
Mode ofpayment
N Valid 47 47 47 47 47 47
Missing 0 0 0 0 0 0
Frequency TableGender of respondent
Frequency Percent Valid PercentCumulative
Percent
Valid Male 40 85.1 85.1 85.1
Female 7 14.9 14.9 100.0
Total 47 100.0 100.0
Level of education
Frequency Percent Valid Percent
Cumulative
Percent
Valid Class IX 1 2.1 2.1 2.1
Class XI/Inter 1 18 38.3 38.3 40.4
Class XII/Inter 2 28 59.6 59.6 100.0
Total 47 100.0 100.0
Name of current service provider
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Frequency Percent Valid PercentCumulative
Percent
Valid Airtel 12 25.5 25.5 25.5
BSNL 8 17.0 17.0 42.6
Hutch 13 27.7 27.7 70.2
Reliance 3 6.4 6.4 76.6
Tata Indicom 11 23.4 23.4 100.0
Total 47 100.0 100.0
Connection Type
Frequency Percent Valid PercentCumulative
Percent
Valid Prepaid 42 89.4 89.4 89.4
Post Paid 5 10.6 10.6 100.0
Total 47 100.0 100.0
Monthly Recharge frequency
Frequency Percent Valid PercentCumulative
Percent
Valid Less than once 3 6.4 6.4 6.4
Once 41 87.2 87.2 93.6
Twice 2 4.3 4.3 97.9
Three or more 1 2.1 2.1 100.0
Total 47 100.0 100.0
Mode of payment
Frequency Percent Valid Percent
Cumulative
PercentValid Cash 45 95.7 95.7 95.7
Cheque 1 2.1 2.1 97.9
Instrument 1 2.1 2.1 100.0
Total 47 100.0 100.0
QUICK CLUSTERmntspend billsms billothr billtalk billfix/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(10) CONVERGE(0)/METHOD=KMEANS(NOUPDATE)/PRINT INITIAL.
Quick ClusterInitial Cluster Centers
Cluster
1 2 3
Monthly expenditure onphone 1000.00 2000.00 99.00
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SMS bill 25.00 40.00 25.00
Other charges .00 .00 .00
Voice calls bill 75.00 60.00 75.00
Fixed component of bill 25.00 70.00 50.00
Iteration History(a)
Iteration
Change in Cluster Centers
1 2 3
1 252.234 .000 216.653
2 .000 .000 .000
a Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change forany center is .000. The current iteration is 2. The minimum distance between initial centers is 901.347.
Final Cluster Centers
Cluster
1 2 3
Monthly expenditure onphone 750.00 2000.00 313.24
SMS bill 35.00 40.00 27.26
Other charges 2.50 .00 3.95
Voice calls bill 43.75 60.00 43.10
Fixed component of bill 31.25 70.00 48.64
Number of Cases in each Cluster
Cluster 1 4.000
2 1.000
3 42.000
Valid 47.000
Missing .000
// Begin here
Clusters based on monthly expenditure on phone is made using K-means method.
The following clusters are obtained. Cluster 2 has the maximum expenditure.
FILTER OFF.USE ALL.EXECUTE .QUICK CLUSTER
mntspend billsms billothr billtalk billfix/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(10) CONVERGE(0)/METHOD=KMEANS(NOUPDATE)/PRINT INITIAL.
Quick Cluster[DataSet1] C:\Users\Dell\Downloads\Cell_Inter.sav
Initial Cluster Centers
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Cluster
1 2 3
Monthly expenditure onphone 1000.00 2000.00 99.00
SMS bill 25.00 40.00 10.00
Other charges .00 .00 .00
Voice calls bill 75.00 60.00 10.00
Fixed component of bill 25.00 70.00 80.00
Iteration History(a)
Iteration
Change in Cluster Centers
1 2 3
1 267.544 .000 225.437
2 .000 .000 .000
a Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change forany center is .000. The current iteration is 2. The minimum distance between initial centers is 905.139.
Final Cluster Centers
Cluster
1 2 3
Monthly expenditure onphone 734.69 2000.00 318.14
SMS bill 27.85 40.00 26.65
Other charges 3.08 .00 5.77
Voice calls bill 46.54 60.00 48.54
Fixed component of bill 44.08 70.00 48.29
It reduced the distance between the clusters centers after the maximum absolute coordinate change for any center is
obtained as .000. Now the three clusters with the changed mean value are obtained as above.
Number of Cases in each Cluster
Cluster 1 13.000
2 1.000
3 192.000
Valid 206.000
Missing .000
VARIABLES=mntspend /COMPARE VARIABLE/PLOT=BOXPLOT/STATISTICS=NONE/NOTOTAL/MISSING=LISTWISE .
It could be seen that some cases are outliers and extremes, to make theconsistent clusters these were removed. A boxplot was made to see this.
ExploreCase Processing Summary
Cases
Valid Missing Total
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N Percent N Percent N Percent
Monthly expenditureon phone 206 100.0% 0 .0% 206 100.0%
Monthly expenditure on phone
2000.00
1500.00
1000.00
500.00
0.00
39
30
121
76
154
10435
81
134
277
89151
USE ALL.COMPUTE filter_$=(mntspend < 600).VARIABLE LABEL filter_$ 'mntspend < 600 (FILTER)'.VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.FORMAT filter_$ (f1.0).FILTER BY filter_$.EXECUTE .
QUICK CLUSTERmntspend billsms billothr billtalk billfix/MISSING=LISTWISE/CRITERIA= CLUSTER(3) MXITER(10) CONVERGE(0)
/METHOD=KMEANS(NOUPDATE)/PRINT INITIAL.The data was filtered and the filter criterion was the monthly expenditureless than Rs. 600 was kept and the expenditure above this was kept aside.
Quick ClusterInitial Cluster Centers
Cluster
1 2 3
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Monthly expenditure onphone 330.00 550.00 99.00
SMS bill .00 70.00 40.00
Other charges .00 .00 .00
Voice calls bill 100.00 20.00 40.00
Fixed component of bill 90.00 35.00 20.00
Iteration History(a)
Iteration
Change in Cluster Centers
1 2 3
1 71.530 72.482 97.952
2 12.762 7.535 19.970
3 .000 .000 .000
a Convergence achieved due to no or small change in cluster centers. The maximum absolute coordinate change forany center is .000. The current iteration is 3. The minimum distance between initial centers is 250.450.
Final Cluster Centers
Cluster
1 2 3
Monthly expenditure onphone 339.50 488.56 208.52
SMS bill 27.66 31.48 22.57
Other charges 6.41 5.07 4.39
Voice calls bill 45.69 49.63 53.61
Fixed component of bill 46.34 43.63 53.41
The above data tables were obtained on again taking out K-Means clusters. Out of 206 cases, 9 were kept aside.Number of Cases in each Cluster
Cluster 1 116.000
2 27.000
3 54.000
Valid 197.000
Missing .000
sort cases by QCL_2 (a) .SORT CASES BY QCL_2 .SPLIT FILELAYERED BY QCL_2 .
.The 9 extremes were manually kept in cluster 2 as it was the cluster of high
expenditure. And a new variable of clusters was added in the table. We pickthe cluster 2, from the above table it is clear that this group has thehighest expenditure on the phone.
CROSSTABS/TABLES=QCL_2 BY contype/FORMAT= AVALUE TABLES/CELLS= COUNT ROW COLUMN/COUNT ROUND CELL .
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Crosstabs[DataSet1] C:\Users\Dell\Downloads\Cell_Inter.sav
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Cluster Number of Case *Connection Type 197 95.6% 9 4.4% 206 100.0%
Cluster Number of Case * Connection Type Crosstabulation
Connection Type Total
Prepaid Post Paid Prepaid
Cluster Numberof Case
1 Count 110 6 116
% within Cluster Number ofCase 94.8% 5.2% 100.0%
% within Connection Type 61.1% 35.3% 58.9%
2 Count 23 4 27
% within Cluster Number ofCase 85.2% 14.8% 100.0%
% within Connection Type 12.8% 23.5% 13.7%
3 Count 47 7 54
% within Cluster Number ofCase 87.0% 13.0% 100.0%
% within Connection Type 26.1% 41.2% 27.4%
Total Count 180 17 197
% within Cluster Number ofCase 91.4% 8.6% 100.0%
% within Connection Type 100.0% 100.0% 100.0%
It is clear from the above table that the more people falling in cluster 2 have the Post paid connection as compared tothe other type of connection. Here by, we make an assumption that people having high expenditure on phone usuallyhave the post paid connection.CROSSTABS/TABLES=contype BY funused5/FORMAT= AVALUE TABLES/CELLS= COUNT ROW COLUMN/COUNT ROUND CELL .
Crosstabs
[DataSet1] C:\Users\Dell\Downloads\Cell_Inter.savCase Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
ConnectionType * Games 206 100.0% 0 .0% 206 100.0%
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Connection Type * Games Crosstabulation
Games Total
Yes No Yes
ConnectionType
Prepaid Count 158 26 184
% within Connection Type 85.9% 14.1% 100.0%
% within Games 88.8% 92.9% 89.3%Post Paid Count 20 2 22
% within Connection Type 90.9% 9.1% 100.0%
% within Games 11.2% 7.1% 10.7%
Total Count 178 28 206
% within Connection Type 86.4% 13.6% 100.0%
% within Games 100.0% 100.0% 100.0%
The above cross tab shows that majority of post paid subscribers play games as compared to the pre paidconnection. Hence, it could be deducted that the cluster 2 people have high phone expenditure, prefer post paidplans and play games.CROSSTABS
/TABLES=QCL_2 BY funused0/FORMAT= AVALUE TABLES/CELLS= COUNT ROW COLUMN/COUNT ROUND CELL .
Crosstabs[DataSet1] C:\Users\Dell\Downloads\Cell_Inter.sav
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Cluster Numberof Case * SMS 197 95.6% 9 4.4% 206 100.0%
Cluster Number of Case * SMS Crosstabulation
SMS Total
Yes No Yes
Cluster Numberof Case
1 Count 103 13 116
% within ClusterNumber of Case 88.8% 11.2% 100.0%
% within SMS 57.5% 72.2% 58.9%
2 Count 26 1 27
% within ClusterNumber of Case 96.3% 3.7% 100.0%
% within SMS 14.5% 5.6% 13.7%
3 Count 50 4 54
% within ClusterNumber of Case 92.6% 7.4% 100.0%
% within SMS 27.9% 22.2% 27.4%
Total Count 179 18 197
% within ClusterNumber of Case
90.9% 9.1% 100.0%
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% within SMS 100.0% 100.0% 100.0%
The above cross tab shows that the cluster 2 people (96.3%) do use SMS service,
which is significantly higher than that of the pre paid users. Uptil here, we get that
CLUSTER 2 people spend the highest on the phone, like games and SMS services
and have postpaid plan.