Studi Kasus 1

PENGHAYATAN ATAS STUDI KASUS DALAM IBM SPSS STATISTICS

STATISTIK DESKRIPTIF

Oleh :

Abdullah M. Jaubah

Pendahuluan

Studi dan penghayatan atas statistik dapat dilakukan melalui studi dan penghayatan atas studi

kasus dalam IBM SPSS Statistics. Studi kasus ini tersedia secara lengkap dalam IBM SPSS

Statistics dan memakai cara point and click. Cara ini mencipta secara otomatis bahasa

perintah dalam bentuk sintaksis. Pembahasan ini mengacu pada studi kasus dan sintaksis

yang dicipta dikumpulkan di sini dalam beberapa bagian. Studi kasus dalam IBM SPSS

Statistics juga mengandung penjelasan lengkap mengenai hasil-hasil dari cara point and click.

Hal ini berarti bahwa hubungan terdapat antara cara point and click dan cara pemrograman

dengan bahasa perintah dalam IBM SPSS Statistics.

Isi pembahasan ini dapat ditelusuri kembali dalam Case Studies IBM SPSS Statistics, karena

penghayatan atas studi kasus ini dapat memperluas pengetahuan mengenai statistik. Studi

kasus ini dilakukan berdasar atas pertanyaan mengapakah dalam IBM SPSS Statistics itu

terdapat banyak sekali arsip data?

Arsip data yang tersedia dalam IBM SPSS Statistics itu ternyata dipakai dalam Case Studies

sehingga penulis melakukan penghayatan atas case studies tersebut.

Data Dalam IBM SPSS Statistics

Beberapa arsip data dipakai di sini yaitu arsip data Contracts.sav, Telco.sav, Aflatoxin.sav,

Ceramics.sav, Satisf.sav, Demo.sav, Site.sav, dan arsip data Marketvalues. Sav. Arsip-arsip

data ini tersedia dalam IBM SPSS Statistics sehingga beberapa arsip data ini tidak disajikan

di sini.

Descriptive Statistics

Descriptive Statistics dalam IBM SPSS Statistics mencakup Frequencies, Descriptives,

Explore, Crosstabs, Ratios, P-P Plots, dan Q-Q Plots. Studi kasus hanya mencakup

Frequencies, Descriptives, Explore, Crosstabs, Ratios saja. Sintaksis yang dikumpulkan dari

1

Case Studies ini disajikan dalam rangka memperkenalkan ketangguhan pemakaian arsip

sintaksis dalam IBM SPSS Statistics sedangkan penjelasan atas hasil dari sintaksis ini dapat

diperoleh melalui studi dan penghayatan Case Studies itu sendiri.

Sintaksis descriptive statistics ini dikumpulkan dari pelaksanaan Case Studies IBM SPSS

Statistics. Sintaksis descriptive statistics ini adalah sebagai berikut :

*************************************************************************** ABDULLAH M. JAUBAH***** FREQUENCIES**********************************************************************

GET FILE='D:\SPSS\CONTACTS.SAV'.

FREQUENCIES VARIABLES=DEPT /PIECHART /ORDER= ANALYSIS .

FREQUENCIES VARIABLES=DEPT /FORMAT=DFREQ /BARCHART /ORDER= ANALYSIS .

FREQUENCIES VARIABLES= RANK /FORMAT=DVALUE /BARCHART /ORDER= ANALYSIS .

FREQUENCIES VARIABLES=SALE /FORMAT=NOTABLE /NTILES= 4 /HISTOGRAM= NORMAL /STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIANSKEWNESS KURTOSIS /ORDER= ANALYSIS .

COMPUTE LOGSALE = LN(SALE).EXECUTE.

FREQUENCIES VARIABLES=LOGSALE /FORMAT=NOTABLE /NTILES= 4 /HISTOGRAM=NORMAL /STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIANSKEWNESS KURTOSIS /ORDER= ANALYSIS .

*************************************************************************** ABDULLAH M. JAUBAH***** DESCRIPTIVES**********************************************************************

GET FILE='D:\SPSS\TELCO.SAV'.

2

DESCRIPTIVES VARIABLES=LONGMON TOLLMON EQUIPMON CARDMON WIREMON /STATISTICS=MEAN STDDEV MIN MAX .

RECODE LONGMON TOLLMON EQUIPMON CARDMON WIREMON (0=SYSMIS) .EXECUTE .

DESCRIPTIVES VARIABLES=LONGMON TOLLMON EQUIPMON CARDMON WIREMON /STATISTICS=MEAN STDDEV SKEWNESS KURTOSIS .

DESCRIPTIVES VARIABLES=LOGLONG LOGTOLL LOGEQUI LOGCARD LOGWIRE /STATISTICS=MEAN STDDEV SKEWNESS KURTOSIS /SAVE .

EXAMINE VARIABLES=ZLOGLONG ZLOGTOLL ZLOGEQUI ZLOGCARD ZLOGWIRE /COMPARE VARIABLE /PLOT=BOXPLOT /STATISTICS=NONE /NOTOTAL /MISSING=PAIRWISE.

*************************************************************************** ABDULLAH M. JAUBAH***** EXPLORE**********************************************************************

GET FILE='D:\SPSS\AFLATOXIN.SAV'.

EXAMINE VARIABLES=TOXIN BY YIELD /PLOT BOXPLOT STEMLEAF /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.

GET FILE='D:\SPSS\CERAMICS.SAV'.

EXAMINE VARIABLES=TEMP BY BATCH /ID= LABRUNID /PLOT BOXPLOT STEMLEAF NPPLOT /COMPARE GROUP /MESTIMATORS HUBER(1.339) ANDREW(1.34) HAMPEL(1.7,3.4,8.5) TUKEY(4.685) /STATISTICS DESCRIPTIVES EXTREME /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.

*************************************************************************** ABDULLAH M. JAUBAH***** CROSSTABS**********************************************************************

GET FILE='D:\SPSS\SATISF.SAV'.

CROSSTABS /TABLES=STORE BY SERVICE /FORMAT= AVALUE TABLES /STATISTIC=CHISQ CC PHI LAMBDA UC /CELLS= COUNT .

CROSSTABS

3

/TABLES=STORE BY SERVICE BY CONTACT /FORMAT= AVALUE TABLES /STATISTIC=CHISQ CC PHI LAMBDA UC /CELLS= COUNT .

CROSSTABS /TABLES=REGULAR BY OVERALL /FORMAT= AVALUE TABLES /STATISTIC=D BTAU CTAU GAMMA /CELLS= COUNT .

GET FILE='D:\SPSS\DEMO.SAV'.

CROSSTABS /TABLES=NEWS BY RESPONSE /FORMAT= AVALUE TABLES /STATISTIC= RISK /CELLS= COUNT ROW.

CROSSTABS /TABLES=NEWS BY RESPONSE BY INCCAT /FORMAT= AVALUE TABLES /STATISTIC=RISK CMH(1) /CELLS= COUNT .

GET FILE='D:\SPSS\SITE.SAV'.

CROSSTABS /TABLES=CONS1 BY CONS2 /FORMAT= AVALUE TABLES /STATISTIC=KAPPA /CELLS= COUNT .


CROSSTABS /TABLES=EMPCAT BY JOBSAT /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COLUMN BPROP /COUNT ROUND CELL.

*************************************************************************** ABDULLAH M. JAUBAH***** SUMMARIES REPORTS**********************************************************************

GET FILE='D:\SPSS\MARKETVALUES.SAV'.

SUMMARIZE /TABLES=VALUE BY STREET /FORMAT=NOLIST TOTAL /TITLE='HOME SALE STATISTICS' /FOOTNOTE 'GROUPED BY STREET' /MISSING=VARIABLE /CELLS=COUNT MEAN MEDIAN MIN MAX .

USE ALL.COMPUTE FILTER_$=(VALUE >=335000).VARIABLE LABEL FILTER_$ 'VALUE >=335000 (FILTER)'.VALUE LABELS FILTER_$ 0 'NOT SELECTED' 1 'SELECTED'.FORMAT FILTER_$ (F1.0).FILTER BY FILTER_$.EXECUTE .

4

SORT CASES BY VALUE (D) MARKTIME (D) .

SUMMARIZE /TABLES=ADDRESS VALUE MARKTIME /FORMAT=VALIDLIST NOCASENUM MISSING='UNAVAILABLE' TOTAL /TITLE='CASE LISTING' /FOOTNOTE 'ONLY HOMES SELLING FOR $335,000 OR MORE' /MISSING=VARIABLE /CELLS=COUNT MEAN MEDIAN .

Hasil Pelaksanaan Sintaksis

Hasil pelaksanaan sintaksis disajikan secara lengkap dan tidak hanya hasil yang dianggap

penting saja. Hasil pelaksanaan sintaksis secara lengkap dapat disajikan di bawah ini :

*************************************************************************** ABDULLAH M. JAUBAH***** FREQUENCIES**********************************************************************

GET FILE='D:\SPSS\CONTACTS.SAV'.

FREQUENCIES VARIABLES=DEPT /PIECHART /ORDER= ANALYSIS .

Statistics

dept

NValid 62

Missing 8

dept Department

Frequency Percent Valid Percent Cumulative Percent

Valid

1 Development 16 22.9 25.8 25.8

2 Computer services 30 42.9 48.4 74.2

3 Finance 13 18.6 21.0 95.2

4 Other 3 4.3 4.8 100.0

Total 62 88.6 100.0

Missing 9 Don't know 8 11.4

Total 70 100.0

5

FREQUENCIES VARIABLES=DEPT /FORMAT=DFREQ /BARCHART /ORDER= ANALYSIS .

Statistics

dept

NValid 62

Missing 8

dept Department


Valid

2 Computer services 30 42.9 48.4 48.4

1 Development 16 22.9 25.8 74.2

3 Finance 13 18.6 21.0 95.2

4 Other 3 4.3 4.8 100.0

Total 62 88.6 100.0


Total 70 100.0

6

FREQUENCIES VARIABLES= RANK /FORMAT=DVALUE /BARCHART /ORDER= ANALYSIS .

Statistics

rank

NValid 59

Missing 11

rank Company rank


Valid

5 Pres/CEO/CFO 6 8.6 10.2 10.2

4 VP 13 18.6 22.0 32.2

3 Sr. manager 18 25.7 30.5 62.7

2 Jr. manager 11 15.7 18.6 81.4

1 Employee 11 15.7 18.6 100.0

Total 59 84.3 100.0


Total 70 100.0

7

FREQUENCIES VARIABLES=SALE /FORMAT=NOTABLE /NTILES= 4 /HISTOGRAM= NORMAL /STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIANSKEWNESS KURTOSIS /ORDER= ANALYSIS .

Statistics

sale

NValid 70

Missing 0

Mean 55.4500

Median 24.0000

Std. Deviation 103.93940

Skewness 5.325

Kurtosis 34.292

Minimum 6.00

Maximum 776.50

Percentiles

25 12.0000

50 24.0000

75 52.8750

8

COMPUTE LOGSALE = LN(SALE).EXECUTE.

FREQUENCIES VARIABLES=LOGSALE /FORMAT=NOTABLE /NTILES= 4 /HISTOGRAM=NORMAL /STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIANSKEWNESS KURTOSIS /ORDER= ANALYSIS .

Statistics

LOGSALE

NValid 70

Missing 0

Mean 3.3373

Median 3.1772


Skewness .721

Kurtosis .367

Minimum 1.79

Maximum 6.65

Percentiles

25 2.4849

50 3.1772

75 3.9679

9

*************************************************************************** ABDULLAH M. JAUBAH***** DESCRIPTIVES**********************************************************************

GET FILE='D:\SPSS\TELCO.SAV'.

DESCRIPTIVES VARIABLES=LONGMON TOLLMON EQUIPMON CARDMON WIREMON /STATISTICS=MEAN STDDEV MIN MAX .


N Minimum Maximum Mean Std. Deviation

longmon 1000 .90 99.95 11.7231 10.36349

tollmon 1000 .00 173.00 13.2740 16.90212

equipmon 1000 .00 77.70 14.2198 19.06854

cardmon 1000 .00 109.25 13.7810 14.08450

wiremon 1000 .00 111.95 11.5839 19.71943

Valid N (listwise) 1000

RECODE LONGMON TOLLMON EQUIPMON CARDMON WIREMON (0=SYSMIS) .EXECUTE .

10

DESCRIPTIVES VARIABLES=LONGMON TOLLMON EQUIPMON CARDMON WIREMON /STATISTICS=MEAN STDDEV SKEWNESS KURTOSIS .


N Mean Std. Deviation Skewness Kurtosis

Statistic Std. Erro

r

Statistic Std. Error

Statistic Std. Error Statistic Std. Error Statistic Std. Error

longmon 1000

11.723

10.363

2.966 0.077 14.052 0.155

tollmon 475

27.945

13.829

3.465 0.112 26.735 0.224

equipmon 386

36.839

10.396

0.756 0.124 0.641 0.248

cardmon 678

20.326

12.629

2.15 0.094 7.572 0.187

wiremon 296

39.135

15.329

1.359 0.142 3.079 0.282Valid N (listwise) 131

DESCRIPTIVES VARIABLES=LOGLONG LOGTOLL LOGEQUI LOGCARD LOGWIRE /STATISTICS=MEAN STDDEV SKEWNESS KURTOSIS /SAVE .


N Mean Std. Deviation Skewness Kurtosis

Statistic Std. Erro

r

Statistic Std. Erro

r

Statistic Std. Erro

r

Statistic Std. Error Statistic Std. Error

loglong 1000 2.1821 0.73455 0.166 0.08 -0.001 0.16

logtoll 475 3.2397 0.41381 0.304 0.11 1.107 0.22

logequi 386 3.5681 0.27756 0.037 0.12 -0.344 0.25

logcard 678 2.8542 0.55729 0.081 0.09 0.109 0.19

logwire 296 3.5983 0.36729 0.2 0.14 -0.168 0.28Valid N (listwise) 131

EXAMINE VARIABLES=ZLOGLONG ZLOGTOLL ZLOGEQUI ZLOGCARD ZLOGWIRE /COMPARE VARIABLE /PLOT=BOXPLOT /STATISTICS=NONE /NOTOTAL /MISSING=PAIRWISE.

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Zloglong 1000 100.0% 0 0.0% 1000 100.0%

Zlogtoll 475 47.5% 525 52.5% 1000 100.0%

Zlogequi 386 38.6% 614 61.4% 1000 100.0%

Zlogcard 678 67.8% 322 32.2% 1000 100.0%

Zlogwire 296 29.6% 704 70.4% 1000 100.0%

11

*************************************************************************** ABDULLAH M. JAUBAH***** EXPLORE**********************************************************************

GET FILE='D:\SPSS\AFLATOXIN.SAV'.

EXAMINE VARIABLES=TOXIN BY YIELD /PLOT BOXPLOT STEMLEAF /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.

12


yield Cases

Valid Missing Total


toxin

1 16 100.0% 0 0.0% 16 100.0%

2 16 100.0% 0 0.0% 16 100.0%

3 16 100.0% 0 0.0% 16 100.0%

4 16 100.0% 0 0.0% 16 100.0%

5 16 100.0% 0 0.0% 16 100.0%

6 16 100.0% 0 0.0% 16 100.0%

7 16 100.0% 0 0.0% 16 100.0%

8 16 100.0% 0 0.0% 16 100.0%

Descriptives

yield Statistic Std. Error

toxin

1

Mean 20.2500 1.07819

95% Confidence Interval for

Mean

Lower Bound 17.9519

Upper Bound 22.5481

5% Trimmed Mean 20.4444

Median 21.5000

Variance 18.600


Minimum 12.00

Maximum 25.00

Range 13.00

Interquartile Range 8.00

Skewness -.788 .564

Kurtosis -.655 1.091

2 Mean 33.0625 3.04339


Mean

Lower Bound 26.5757

Upper Bound 39.5493


Median 29.0000

Variance 148.196


Minimum 22.00

Maximum 68.00

Range 46.00


Skewness 1.898 .564

13

Kurtosis 3.880 1.091

3

Mean 32.6875 2.57669


Mean

Lower Bound 27.1954

Upper Bound 38.1796


Median 30.5000

Variance 106.229


Minimum 16.00

Maximum 52.00

Range 36.00


Skewness .589 .564


4

Mean 14.6875 .66281


Mean

Lower Bound 13.2747

Upper Bound 16.1003


Median 14.5000

Variance 7.029


Minimum 11.00

Maximum 19.00

Range 8.00


Skewness .116 .564

Kurtosis -1.393 1.091

5

Mean 33.0000 1.55724


Mean

Lower Bound 29.6808

Upper Bound 36.3192


Median 32.0000

Variance 38.800


Minimum 25.00

Maximum 49.00

Range 24.00


Skewness 1.021 .564

Kurtosis 1.536 1.091

6 Mean 31.3750 .71224

95% Confidence Interval for Lower Bound 29.8569

14

Mean Upper Bound 32.8931


Median 32.0000

Variance 8.117


Minimum 26.00

Maximum 37.00

Range 11.00


Skewness -.019 .564


7

Mean 17.0625 1.04670


Mean

Lower Bound 14.8315

Upper Bound 19.2935


Median 17.0000

Variance 17.529


Minimum 9.00

Maximum 25.00

Range 16.00


Skewness -.094 .564

Kurtosis .121 1.091

8

Mean 8.4375 .76903


Mean

Lower Bound 6.7984

Upper Bound 10.0766


Median 7.5000

Variance 9.463


Minimum 4.00

Maximum 14.00

Range 10.00


Skewness .469 .564


Aflatoxin PPB Stem-and-Leaf Plot foryield= 1

Frequency Stem & Leaf

15

2.00 1 . 23 3.00 1 . 559 9.00 2 . 001223444 2.00 2 . 55

Stem width: 10.00 Each leaf: 1 case(s)



4.00 2 . 2234 6.00 2 . 789999 1.00 3 . 3 2.00 3 . 67 1.00 4 . 1 .00 4 . 1.00 5 . 2 1.00 Extremes (>=68)




1.00 1 . 6 6.00 2 . 236678 6.00 3 . 015667 1.00 4 . 8 2.00 5 . 02




2.00 1 . 11 5.00 1 . 22333 2.00 1 . 45 4.00 1 . 6677 3.00 1 . 889




.00 2 . 6.00 2 . 557999 4.00 3 . 1223 4.00 3 . 6678 1.00 4 . 0 1.00 Extremes (>=49)

16




5.00 2 . 68899 9.00 3 . 112222334 2.00 3 . 57




1.00 0 . 9 2.00 1 . 12 9.00 1 . 557777789 3.00 2 . 013 1.00 2 . 5




1.00 0 . 4 10.00 0 . 5567777889 5.00 1 . 12234


17

GET FILE='D:\SPSS\CERAMICS.SAV'.

EXAMINE VARIABLES=TEMP BY BATCH /ID= LABRUNID /PLOT BOXPLOT STEMLEAF NPPLOT /COMPARE GROUP /MESTIMATORS HUBER(1.339) ANDREW(1.34) HAMPEL(1.7,3.4,8.5) TUKEY(4.685) /STATISTICS DESCRIPTIVES EXTREME /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.


batch Cases

Valid Missing Total


temp1 Premium 240 100.0% 0 0.0% 240 100.0%

2 Standard 240 100.0% 0 0.0% 240 100.0%

18

Descriptives

batch Statistic Std. Error

temp

1 Premium

Mean 1542.0787 .61165

95% Confidence Interval for MeanLower Bound 1540.8738

Upper Bound 1543.2836


Median 1539.7181

Variance 89.789


Minimum 1530.44

Maximum 1591.04

Range 60.61


Skewness 1.439 .157

Kurtosis 3.036 .313

2 Standard

Mean 1514.6564 .62004

95% Confidence Interval for MeanLower Bound 1513.4350

Upper Bound 1515.8779


Median 1514.5317

Variance 92.269


Minimum 1488.30

Maximum 1537.99

Range 49.69


Skewness -.078 .157

Kurtosis -.343 .313

M-Estimators

batch Huber's M-Estimatora Tukey's Biweightb Hampel's M-Estimatorc Andrews' Waved

temp1 Premium 1540.0953 1539.5658 1540.2052 1539.5506

2 Standard 1514.6413 1514.6925 1514.6828 1514.6955

a. The weighting constant is 1.339.

b. The weighting constant is 4.685.

c. The weighting constants are 1.700, 3.400, and 8.500

d. The weighting constant is 1.340*pi.

19

Extreme Values

batch Case Number labrunid Value

temp 1 Premium

Highest

1 211 d421 1591.04

2 417 g837 1574.62

3 17 a 17 1571.77

4 437 h917 1568.10

5 357 f657 1567.07

Lowest1 139 c289 1530.44

2 475 h955 1530.73

20

3 199 d379 1530.75

4 373 g733 1530.76

5 207 d387 1530.79

2 Standard

Highest

1 408 g828 1537.99

2 198 d378 1534.29

3 20 a 20 1534.06

4 168 c318 1533.43

5 184 d364 1533.35

Lowest

1 396 g816 1488.30

2 100 b190 1488.36

3 80 b170 1494.09

4 154 c304 1494.64

5 240 d450 1495.15

Tests of Normality

batch Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

temp1 Premium .123 240 .000 .888 240 .000

2 Standard .027 240 .200* .995 240 .602

*. This is a lower bound of the true significance.

a. Lilliefors Significance Correction

temp Degrees Centigrade

Stem-and-Leaf Plots

Degrees Centigrade Stem-and-Leaf Plot forbatch= Premium


24.00 153 . 000000011111111111111111 22.00 153 . 2222222222333333333333 26.00 153 . 44444444445555555555555555 26.00 153 . 66666666666666777777777777 24.00 153 . 888888888888899999999999 19.00 154 . 0000000000111111111 25.00 154 . 2222222222222223333333333 10.00 154 . 4444455555 12.00 154 . 666666667777 10.00 154 . 8888999999 8.00 155 . 00111111 4.00 155 . 2223 6.00 155 . 445555 6.00 155 . 666667 6.00 155 . 888899 3.00 156 . 011 3.00 156 . 223 6.00 Extremes (>=1566)


21

Degrees Centigrade Stem-and-Leaf Plot forbatch= Standard


2.00 148 . 88 2.00 149 . 44 12.00 149 . 566677788999 22.00 150 . 0001111122333333333444 35.00 150 . 55555555666667777777777777888888999 54.00 151 . 000000001111111111112222222333333333333333444444444444 43.00 151 . 5555556666666667777777777777778888899999999 32.00 152 . 00000000011111122223333333334444 22.00 152 . 5555555666667777888899 15.00 153 . 000000122223344 1.00 153 . 7


Normal Q-Q Plots

22

Detrended Normal Q-Q Plots

23

*************************************************************************** ABDULLAH M. JAUBAH***** CROSSTABS**********************************************************************

GET FILE='D:\SPSS\SATISF.SAV'.

CROSSTABS /TABLES=STORE BY SERVICE /FORMAT= AVALUE TABLES /STATISTIC=CHISQ CC PHI LAMBDA UC /CELLS= COUNT .

Crosstabs


Cases

Valid Missing Total


store * service 582 100.0% 0 0.0% 582 100.0%

store Store * service Service satisfaction Crosstabulation

Count service Total

1 Strongly Negative

2 Somewhat Negative

3 Neutral 4 Somewhat Positive

5 Strongly Positive

store

1 Store 1 25 20 38 30 33 146

2 Store 2 26 30 34 27 19 136

3 Store 3 15 20 41 33 29 138

4 Store 4 27 35 44 22 34 162

Total 93 105 157 112 115 582

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 16.293a 12 .178

Continuity Correction

Likelihood Ratio 17.012 12 .149

Linear-by-Linear Association .084 1 .772

N of Valid Cases 582

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 21.73.

Directional Measures

Value Asymp. Std. Errora Approx. Tb Approx. Sig.

25

Nominal by Nominal

Lambda

Symmetric 0.013 0.009 1.486 0.137

store Dependent 0.026 0.017 1.486 0.137

service Dependent 0 0 .c .c

Goodman and Kruskal tau

Symmetric store Dependent 0.009 0.004 .183d

service Dependent 0.007 0.003 .226d

Uncertainty Coefficient

Symmetric 0.01 0.005 2.122 .149e

store Dependent 0.011 0.005 2.122 .149e

service Dependent 0.009 0.004 2.122 .149e

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

c. Cannot be computed because the asymptotic standard error equals zero.

d. Based on chi-square approximation

e. Likelihood ratio chi-square probability.

Symmetric Measures


Nominal by

Nominal

Phi .167 .178

Cramer's V .097 .178

Contingency Coefficient .165 .178




CROSSTABS /TABLES=STORE BY SERVICE BY CONTACT /FORMAT= AVALUE TABLES /STATISTIC=CHISQ CC PHI LAMBDA UC /CELLS= COUNT .


Cases

Valid Missing Total


store * service * contact 582 100.0% 0 0.0% 582 100.0%

store Store * service Service satisfaction * contact Contact with employee Crosstabulation

Count

26

contact service Total

1 Strongly Negative

2 Somewhat Negative


5 Strongly Positive

0 No

store

1 Store 1 16 9 18 17 19 79

2 Store 2 2 15 16 13 12 58

3 Store 3 9 14 23 22 14 82

4 Store 4 17 14 19 10 10 70

Total 44 52 76 62 55 289

1 Yes

store

1 Store 1 9 11 20 13 14 67

2 Store 2 24 15 18 14 7 78

3 Store 3 6 6 18 11 15 56

4 Store 4 10 21 25 12 24 92

Total 49 53 81 50 60 293

Total

store

1 Store 1 25 20 38 30 33 146

2 Store 2 26 30 34 27 19 136

3 Store 3 15 20 41 33 29 138

4 Store 4 27 35 44 22 34 162

Total 93 105 157 112 115 582

Chi-Square Tests

contact Value df Asymp. Sig. (2-sided)

0 No

Pearson Chi-Square 20.898b 12 .052



Linear-by-Linear Association 3.514 1 .061


1 Yes

Pearson Chi-Square 25.726c 12 .012





Total




Linear-by-Linear Association .084 1 .772



b. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.83.

c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 9.37.


contact Value Asymp. Std.

Errora

Approx. Tb Approx. Sig.

27

0 No

Nominal by Nominal

Lambda

Symmetric 0.036 0.03 1.178 0.239

store Dependent 0.068 0.044 1.498 0.134

service Dependent 0.005 0.028 0.164 0.869


Symmetric

store Dependent 0.023 0.009 .067d



Symmetric 0.027 0.01 2.604 .028e



1 Yes

Nominal by Nominal

Lambda

Symmetric 0.053 0.029 1.806 0.071

store Dependent 0.08 0.037 2.081 0.037

service Dependent 0.028 0.03 0.927 0.354


Symmetric




Symmetric 0.03 0.011 2.605 .012e



Total

Nominal by Nominal

Lambda

Symmetric 0.013 0.009 1.486 0.137

store Dependent 0.026 0.017 1.486 0.137

service Dependent 0 0 .c .c


Symmetric




Symmetric 0.01 0.005 2.122 .149e





c. Cannot be computed because the asymptotic standard error equals zero.

d. Based on chi-square approximation

e. Likelihood ratio chi-square probability.

Symmetric Measures

contact Value Asymp. Std. Errora Approx. Tb Approx. Sig.

0 NoNominal by

Phi 0.269 0.052

Cramer's V 0.155 0.052

28

Nominal Contingency Coefficient 0.26 0.052


1 Yes

Nominal by Nominal

Phi 0.296 0.012

Cramer's V 0.171 0.012

Contingency Coefficient 0.284 0.012


Total

Nominal by Nominal

Phi 0.167 0.178

Cramer's V 0.097 0.178

Contingency Coefficient 0.165 0.178

N of Valid Cases 582 a. Not assuming the null hypothesis.


CROSSTABS /TABLES=REGULAR BY OVERALL /FORMAT= AVALUE TABLES /STATISTIC=D BTAU CTAU GAMMA /CELLS= COUNT .


Cases

Valid Missing Total


regular * overall 582 100.0% 0 0.0% 582 100.0%

regular Shopping frequency * overall Overall satisfaction Crosstabulation

Count overall Total

1 Strongly Negative

2 Somewhat Negative


5 Strongly Positive

regular

0 First time 5 13 15 14 5 521 < 1/month 26 38 39 34 16 153

2 1/month 27 43 46 55 30 201

3 1/week 7 36 33 40 26 142

4 > 1/week 1 8 10 5 10 34

Total 66 138 143 148 87 582


Value Asymp. Std. Errora

Approx. Tb Approx. Sig.

Ordinal by Somers' d

Symmetric 0.107 0.033 3.267 0.001

regular Dependent 0.104 0.032 3.267 0.001

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Ordina overall Dependent 0.11 0.034 3.267 0.001a. Not assuming the null hypothesis.


Symmetric Measures


Ordinal by Ordinal

Kendall's tau-b .107 .033 3.267 .001

Kendall's tau-c .102 .031 3.267 .001

Gamma .140 .043 3.267 .001





CROSSTABS /TABLES=NEWS BY RESPONSE /FORMAT= AVALUE TABLES /STATISTIC= RISK /CELLS= COUNT ROW.


Cases

Valid Missing Total


news * response 6400 100.0% 0 0.0% 6400 100.0%

news Newspaper subscription * response Response Crosstabulation

response Total

0 Yes 1 No

news

0 YesCount 380 2388 2768

% within news 13.7% 86.3% 100.0%

1 NoCount 299 3333 3632

% within news 8.2% 91.8% 100.0%

TotalCount 679 5721 6400

% within news 10.6% 89.4% 100.0%

Risk Estimate

Value 95% Confidence Interval

Lower Upper

Odds Ratio for news (0 Yes / 1 No) 1.774 1.511 2.082

30

For cohort response = 0 Yes 1.668 1.445 1.924

For cohort response = 1 No .940 .924 .957


CROSSTABS /TABLES=NEWS BY RESPONSE BY INCCAT /FORMAT= AVALUE TABLES /STATISTIC=RISK CMH(1) /CELLS= COUNT .


Cases

Valid Missing Total


news * response * inccat 6400 100.0% 0 0.0% 6400 100.0%

news Newspaper subscription * response Response * inccat Income

category in thousands Crosstabulation

Count

inccat response Total

0 Yes 1 No

1.00 Under $25news

0 Yes 102 319 421

1 No 85 668 753

Total 187 987 1174

2.00 $25 - $49news

0 Yes 135 741 876

1 No 137 1375 1512

Total 272 2116 2388

3.00 $50 - $74news

0 Yes 52 434 486

1 No 33 601 634

Total 85 1035 1120

4.00 $75+news

0 Yes 91 894 985

1 No 44 689 733

Total 135 1583 1718

Totalnews

0 Yes 380 2388 2768

1 No 299 3333 3632

Total 679 5721 6400

Risk Estimate

inccat Value 95% Confidence Interval

Lower Upper

1.00 Under $25 Odds Ratio for news (0 Yes / 1 No) 2.513 1.830 3.451

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2.00 $25 - $49





3.00 $50 - $74





4.00 $75+





Total





Tests of Homogeneity of the Odds Ratio

Chi-Squared df Asymp. Sig. (2-sided)

Breslow-Day 4.030 3 .258

Tarone's 4.026 3 .259

Tests of Conditional Independence

Chi-Squared df Asymp. Sig. (2-sided)

Cochran's 68.916 1 .000

Mantel-Haenszel 68.178 1 .000

Under the conditional independence assumption, Cochran's statistic is asymptotically distributed as a 1 df chi-

squared distribution, only if the number of strata is fixed, while the Mantel-Haenszel statistic is always

asymptotically distributed as a 1 df chi-squared distribution. Note that the continuity correction is removed from

the Mantel-Haenszel statistic when the sum of the differences between the observed and the expected is 0.

Mantel-Haenszel Common Odds Ratio Estimate

Estimate 1.976

ln(Estimate) .681

Std. Error of ln(Estimate) .083

Asymp. Sig. (2-sided) .000

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Asymp. 95% Confidence

Interval

Common Odds RatioLower Bound 1.678

Upper Bound 2.327

ln(Common Odds Ratio)Lower Bound .518

Upper Bound .845

The Mantel-Haenszel common odds ratio estimate is asymptotically normally distributed under

the common odds ratio of 1.000 assumption. So is the natural log of the estimate.

GET FILE='D:\SPSS\SITE.SAV'.

CROSSTABS /TABLES=CONS1 BY CONS2 /FORMAT= AVALUE TABLES /STATISTIC=KAPPA /CELLS= COUNT .


Cases

Valid Missing Total


cons1 * cons2 20 100.0% 0 0.0% 20 100.0%

cons1 Rating from consultant 1 * cons2 Rating from consultant 2

Crosstabulation

Count

cons2 Total

1 Poor 2 Fair 3 Good

cons1

1 Poor 7 0 0 7

2 Fair 5 2 1 8

3 Good 1 0 4 5

Total 13 2 5 20

Symmetric Measures


Measure of Agreement Kappa .478 .138 3.576 .000

N of Valid Cases 20


33



CROSSTABS /TABLES=EMPCAT BY JOBSAT /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COLUMN BPROP /COUNT ROUND CELL.


Cases

Valid Missing Total


empcat * jobsat 6400 100.0% 0 0.0% 6400 100.0%

empcat Years with current employer * jobsat Job satisfaction Crosstabulation

% within jobsat jobsat Total

1 Highly dissatisfied

2 Somewhat dissatisfied

3 Neutral 4 Somewhat satisfied

5 Highly satisfied

empcat

1 Less than 5 74.4%a 44.9%b 31.9%c 18.8%d 9.2%e 34.60%

2 5 to 15 21.2%a 40.5%b 41.9%b 44.1%b 33.7%c 36.90%

3 More than 15 4.4%a 14.7%b 26.2%c 37.1%d 57.0%e 28.40%

Total 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

Each subscript letter denotes a subset of jobsat categories whose column proportions do not differ significantly from each other at the .05 level.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)







*************************************************************************** ABDULLAH M. JAUBAH***** SUMMARIES REPORTS**********************************************************************

GET FILE='D:\SPSS\MARKETVALUES.SAV'.

SUMMARIZE

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/TABLES=VALUE BY STREET /FORMAT=NOLIST TOTAL /TITLE='HOME SALE STATISTICS' /FOOTNOTE 'GROUPED BY STREET' /MISSING=VARIABLE /CELLS=COUNT MEAN MEDIAN MIN MAX .


Cases

Included Excluded Total


value * street 94 100.0% 0 0.0% 94 100.0%

HOME SALE STATISTICS

value

street N Mean Median Minimum Maximum

Bunker Hill Dr 28 $279,821.43 $281,000.00 $200,000 $416,000

Dawson Ln 23 $131,391.30 $132,000.00 $118,000 $140,000

Fairway View Dr 7 $283,000.00 $271,000.00 $243,000 $343,000

Lakeview Dr 8 $304,000.00 $300,500.00 $289,000 $334,000

Par Dr 7 $303,714.29 $305,000.00 $271,000 $349,000

Persimmon Dr 9 $312,111.11 $300,000.00 $281,000 $351,000

Wintergreen Te 12 $322,833.33 $317,500.00 $273,000 $403,000

Total 94 $256,159.57 $281,000.00 $118,000 $416,000

GROUPED BY STREET

USE ALL.COMPUTE FILTER_$=(VALUE >=335000).VARIABLE LABEL FILTER_$ 'VALUE >=335000 (FILTER)'.VALUE LABELS FILTER_$ 0 'NOT SELECTED' 1 'SELECTED'.FORMAT FILTER_$ (F1.0).FILTER BY FILTER_$.EXECUTE .

SORT CASES BY VALUE (D) MARKTIME (D) .

SUMMARIZE /TABLES=ADDRESS VALUE MARKTIME /FORMAT=VALIDLIST NOCASENUM MISSING='UNAVAILABLE' TOTAL /TITLE='CASE LISTING' /FOOTNOTE 'ONLY HOMES SELLING FOR $335,000 OR MORE' /MISSING=VARIABLE /CELLS=COUNT MEAN MEDIAN .


Cases

Included Excluded Total


address 14 100.0% 0 0.0% 14 100.0%

value 14 100.0% 0 0.0% 14 100.0%

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marktime 13 92.9% 1 7.1% 14 100.0%

CASE LISTING

address value marktime

1 3621 Bunker Hill Dr $416,000 62

2 3500 Wintergreen Ter $403,000 55

3 3761 Persimmon Dr $351,000 106

4 3721 Persimmon Dr $349,000 54

5 910 Par Dr $349,000 5

6 3631 Bunker Hill Dr $347,000 133

7 3751 Persimmon Dr $345,000 75


9 521 Fairway View Dr $343,000 49

10 3630 Bunker Hill Dr $342,000 18


12 3510 Wintergreen Ter $336,000 103

13 3520 Bunker Hill Dr $335,000 91

14 701 Fairway View Dr $335,000 UNAVAILABLE

Total

N 14 14 13

Mean $352,285.71 66.59

Median $344,500.00 62.22

ONLY HOMES SELLING FOR $335,000 OR MORE

Rangkuman

Penulis dalam melakukan penghayatan atas sintaksis Case Studies IBM SPSS Statistics hanya

menggabungkan sintaksis yang tersusun secara berurutan dan terpencar-pencar. Data yang

dipakai dalam Case Studies IBM SPSS Statistics tersedia juga dalam IBM SPSS Statistics.

Interpretasi atas hasil-hasil di atas tidak dilakukan di sini dan terdapat dalam pembahasan

Case Studies IBM SPSS Statistics. Penyajian studi kasus ini bukan untuk tujuan komersial

akan tetapi untuk memperkenalkan ketangguhan sintaksis dalam IBM SPSS Statistics.

Penulis mengharap kritik dari para pembaca.

Permata Depok Regency, 20 April 2015

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Studi Kasus 1

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