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Uas Jonatan

The document presents correlation and reliability analyses for two datasets, DataSet0 and DataSet1, using various variables. In DataSet0, significant correlations were found between p1 and x05, and x06, with a Cronbach's Alpha of 0.783 indicating good reliability across 15 items. DataSet1 shows a weaker correlation between VAR00001 and VAR00002, with a Pearson correlation of 0.317 and no significant findings.

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daratumorang06
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5 views11 pages

Uas Jonatan

The document presents correlation and reliability analyses for two datasets, DataSet0 and DataSet1, using various variables. In DataSet0, significant correlations were found between p1 and x05, and x06, with a Cronbach's Alpha of 0.783 indicating good reliability across 15 items. DataSet1 shows a weaker correlation between VAR00001 and VAR00002, with a Pearson correlation of 0.317 and no significant findings.

Uploaded by

daratumorang06
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as RTF, PDF, TXT or read online on Scribd
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CORRELATIONS

/VARIABLES=p1 x02 x03 x04 x05 x06 x07 x08 x09 x10 x11 x12 x13 x14 x15
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.

Correlations

Notes

Output Created 30-JUN-2025 13:42:38


Comments
Input Active Dataset DataSet0
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics for each pair of variables are
based on all the cases with valid data
for that pair.
Syntax CORRELATIONS
/VARIABLES=p1 x02 x03 x04 x05 x06
x07 x08 x09 x10 x11 x12 x13 x14 x15
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.
Resources Processor Time 00:00:00,03

Elapsed Time 00:00:00,03

[DataSet0]

Correlations

p1 x02 x03 x04 x05 x06 x07 x08

p1 Pearson 1 .357 .094 .000 .644** .162 -.313 .015


Correlation
Sig. (2-tailed) .080 .653 1.000 .001 .440 .128 .942

N 25 25 25 25 25 25 25 25
x02 Pearson
.357 1 .283 -.077 .261 .277 .043 .321
Correlation
Sig. (2-tailed) .080 .170 .714 .208 .180 .840 .118
N 25 25 25 25 25 25 25 25
x03 Pearson
.094 .283 1 .102 .223 .947** .263 .263
Correlation
Sig. (2-tailed) .653 .170 .627 .284 .000 .204 .204
N 25 25 25 25 25 25 25 25
x04 Pearson
.000 -.077 .102 1 .281 .175 .123 .017
Correlation
Sig. (2-tailed) 1.000 .714 .627 .173 .404 .559 .938
N 25 25 25 25 25 25 25 25
x05 Pearson
.644** .261 .223 .281 1 .218 -.165 .105
Correlation
Sig. (2-tailed) .001 .208 .284 .173 .295 .432 .618
N 25 25 25 25 25 25 25 25
x06 Pearson
.162 .277 .947** .175 .218 1 .257 .257
Correlation
Sig. (2-tailed) .440 .180 .000 .404 .295 .215 .215
N 25 25 25 25 25 25 25 25
x07 Pearson
-.313 .043 .263 .123 -.165 .257 1 .207
Correlation
Sig. (2-tailed) .128 .840 .204 .559 .432 .215 .322
N 25 25 25 25 25 25 25 25
x08 Pearson
.015 .321 .263 .017 .105 .257 .207 1
Correlation
Sig. (2-tailed) .942 .118 .204 .938 .618 .215 .322
N 25 25 25 25 25 25 25 25
x09 Pearson
.644** .261 .223 .281 1.000** .218 -.165 .105
Correlation
Sig. (2-tailed) .001 .208 .284 .173 .000 .295 .432 .618
N 25 25 25 25 25 25 25 25
x10 Pearson
-.031 .199 .081 -.116 -.178 .154 -.064 .551**
Correlation
Sig. (2-tailed) .884 .340 .700 .581 .396 .464 .761 .004
N 25 25 25 25 25 25 25 25
x11 Pearson
.094 .283 1.000** .102 .223 .947** .263 .263
Correlation
Sig. (2-tailed) .653 .170 .000 .627 .284 .000 .204 .204
N 25 25 25 25 25 25 25 25
x12 Pearson
.189 .283 .875** .204 .223 .947** .263 .263
Correlation
Sig. (2-tailed) .366 .170 .000 .328 .284 .000 .204 .204
N 25 25 25 25 25 25 25 25
x13 Pearson
.337 .184 .122 .199 .260 .094 -.165 -.141
Correlation
Sig. (2-tailed) .099 .379 .562 .341 .210 .654 .432 .501
N 25 25 25 25 25 25 25 25
x14 Pearson
.296 .296 .522** .320 .233 .670** .275 .099
Correlation
Sig. (2-tailed) .151 .151 .007 .119 .262 .000 .184 .639
N 25 25 25 25 25 25 25 25
x15 Pearson
-.031 -.184 .182 -.033 .316 .154 .317 .223
Correlation

Sig. (2-tailed) .884 .379 .383 .875 .124 .464 .123 .284

N 25 25 25 25 25 25 25 25

Correlations

x09 x10 x11 x12 x13 x14 x15

p1 Pearson Correlation .644** -.031 .094 .189 .337 .296 -.031

Sig. (2-tailed) .001 .884 .653 .366 .099 .151 .884

N 25 25 25 25 25 25 25
x02 Pearson Correlation .261 .199 .283 .283 .184 .296 -.184
Sig. (2-tailed) .208 .340 .170 .170 .379 .151 .379
N 25 25 25 25 25 25 25
** ** **
x03 Pearson Correlation .223 .081 1.000 .875 .122 .522 .182
Sig. (2-tailed) .284 .700 .000 .000 .562 .007 .383
N 25 25 25 25 25 25 25
x04 Pearson Correlation .281 -.116 .102 .204 .199 .320 -.033
Sig. (2-tailed) .173 .581 .627 .328 .341 .119 .875
N 25 25 25 25 25 25 25
**
x05 Pearson Correlation 1.000 -.178 .223 .223 .260 .233 .316
Sig. (2-tailed) .000 .396 .284 .284 .210 .262 .124
N 25 25 25 25 25 25 25
** ** **
x06 Pearson Correlation .218 .154 .947 .947 .094 .670 .154
Sig. (2-tailed) .295 .464 .000 .000 .654 .000 .464
N 25 25 25 25 25 25 25
x07 Pearson Correlation -.165 -.064 .263 .263 -.165 .275 .317
Sig. (2-tailed) .432 .761 .204 .204 .432 .184 .123
N 25 25 25 25 25 25 25
x08 Pearson Correlation .105 .551** .263 .263 -.141 .099 .223
Sig. (2-tailed) .618 .004 .204 .204 .501 .639 .284
N 25 25 25 25 25 25 25
x09 Pearson Correlation 1 -.178 .223 .223 .260 .233 .316
Sig. (2-tailed) .396 .284 .284 .210 .262 .124
N 25 25 25 25 25 25 25
x10 Pearson Correlation -.178 1 .081 .182 -.342 .120 .013
Sig. (2-tailed) .396 .700 .383 .094 .568 .950
N 25 25 25 25 25 25 25
x11 Pearson Correlation .223 .081 1 .875** .122 .522** .182
Sig. (2-tailed) .284 .700 .000 .562 .007 .383
N 25 25 25 25 25 25 25
** **
x12 Pearson Correlation .223 .182 .875 1 .020 .740 .081
Sig. (2-tailed) .284 .383 .000 .923 .000 .700
N 25 25 25 25 25 25 25
x13 Pearson Correlation .260 -.342 .122 .020 1 .056 -.095
Sig. (2-tailed) .210 .094 .562 .923 .789 .650
N 25 25 25 25 25 25 25
** **
x14 Pearson Correlation .233 .120 .522 .740 .056 1 -.056
Sig. (2-tailed) .262 .568 .007 .000 .789 .789
N 25 25 25 25 25 25 25
x15 Pearson Correlation .316 .013 .182 .081 -.095 -.056 1

Sig. (2-tailed) .124 .950 .383 .700 .650 .789

N 25 25 25 25 25 25 25

**. Correlation is significant at the 0.01 level (2-tailed).

RELIABILITY
/VARIABLES=p1 x02 x03 x04 x05 x06 x07 x08 x09 x10 x11 x12 x13 x14 x15
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA.

Reliability

Notes

Output Created 30-JUN-2025 13:43:50


Comments
Input Active Dataset DataSet0
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Matrix Input
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics are based on all cases with
valid data for all variables in the
procedure.
Syntax RELIABILITY
/VARIABLES=p1 x02 x03 x04 x05 x06
x07 x08 x09 x10 x11 x12 x13 x14 x15
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA.
Resources Processor Time 00:00:00,02

Elapsed Time 00:00:00,01

Scale: ALL VARIABLES

Case Processing Summary

N %

Cases Valid 25 100.0

Excludeda 0 .0

Total 25 100.0

a. Listwise deletion based on all variables in the


procedure.

Reliability Statistics

Cronbach's
Alpha N of Items

.783 15
NEW FILE.
DATASET NAME DataSet1 WINDOW=FRONT.
CORRELATIONS
/VARIABLES=VAR00001 VAR00002
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.

Correlations

Notes

Output Created 30-JUN-2025 13:47:20


Comments
Input Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics for each pair of variables are
based on all the cases with valid data
for that pair.
Syntax CORRELATIONS
/VARIABLES=VAR00001 VAR00002
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.
Resources Processor Time 00:00:00,02

Elapsed Time 00:00:00,01

[DataSet1]

Correlations

VAR00001 VAR00002
VAR00001 Pearson Correlation 1 .317

Sig. (2-tailed) .123

N 25 25
VAR00002 Pearson Correlation .317 1

Sig. (2-tailed) .123

N 25 25

RELIABILITY
/VARIABLES=VAR00001 VAR00002
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA.

Reliability

Notes

Output Created 30-JUN-2025 13:48:10


Comments
Input Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Matrix Input
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics are based on all cases with
valid data for all variables in the
procedure.
Syntax RELIABILITY
/VARIABLES=VAR00001 VAR00002
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA.
Resources Processor Time 00:00:00,00

Elapsed Time 00:00:00,01


Scale: ALL VARIABLES

Case Processing Summary

N %

Cases Valid 25 100.0

Excludeda 0 .0

Total 25 100.0

a. Listwise deletion based on all variables in the


procedure.

Reliability Statistics

Cronbach's
Alpha N of Items

.160 2

REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT VAR00001
/METHOD=ENTER VAR00002
/SAVE RESID.

Regression

Notes

Output Created 30-JUN-2025 15:23:00


Comments
Input Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics are based on cases with no
missing values for any variable used.
Syntax REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R
ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT VAR00001
/METHOD=ENTER VAR00002
/SAVE RESID.
Resources Processor Time 00:00:00,03
Elapsed Time 00:00:00,03
Memory Required 1356 bytes
Additional Memory Required
0 bytes
for Residual Plots
Variables Created or RES_1
Unstandardized Residual
Modified

Variables Entered/Removeda

Variables Variables
Model Entered Removed Method
b
1 VAR00002 . Enter

a. Dependent Variable: VAR00001


b. All requested variables entered.

Model Summaryb

Adjusted R Std. Error of the


Model R R Square Square Estimate
a
1 .317 .100 .061 .68972

a. Predictors: (Constant), VAR00002


b. Dependent Variable: VAR00001
ANOVAa

Model Sum of Squares df Mean Square F Sig.

1 Regression 1.219 1 1.219 2.562 .123b

Residual 10.941 23 .476

Total 12.160 24

a. Dependent Variable: VAR00001


b. Predictors: (Constant), VAR00002

Coefficientsa

Standardized
Unstandardized Coefficients Coefficients

Model B Std. Error Beta t Sig.

1 (Constant) 1.417 1.271 1.115 .277

VAR00002 .044 .028 .317 1.601 .123

a. Dependent Variable: VAR00001

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 3.1442 4.0742 3.4400 .22534 25


Residual -1.45417 .81153 .00000 .67519 25
Std. Predicted Value -1.313 2.814 .000 1.000 25
Std. Residual -2.108 1.177 .000 .979 25

a. Dependent Variable: VAR00001

NPAR TESTS
/K-S(NORMAL)=RES_1
/MISSING ANALYSIS.

NPar Tests
Notes

Output Created 30-JUN-2025 15:23:20


Comments
Input Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
25
File
Missing Value Handling Definition of Missing User-defined missing values are treated
as missing.
Cases Used Statistics for each test are based on all
cases with valid data for the variable(s)
used in that test.
Syntax NPAR TESTS
/K-S(NORMAL)=RES_1
/MISSING ANALYSIS.
Resources Processor Time 00:00:00,02

Elapsed Time 00:00:00,01


a
Number of Cases Allowed 196608

a. Based on availability of workspace memory.

One-Sample Kolmogorov-Smirnov Test

Unstandardized
Residual

N 25
a,b
Normal Parameters Mean .0000000
Std. Deviation .67519434
Most Extreme Differences Absolute .187
Positive .115
Negative -.187
Test Statistic .187
Asymp. Sig. (2-tailed) .024c

a. Test distribution is Normal.


b. Calculated from data.
c. Lilliefors Significance Correction.

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