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y Pearson Correlation 1 .035 .417 ** .644 ** .652 ** .042 -.320 *

Sig. (2-tailed) .807 .003 .000 .000 .775 .023

N 50 50 50 50 50 50 50

x1 Pearson Correlation .035 1 -.125 .078 .108 -.042 .178

Sig. (2-tailed) .807 .387 .591 .455 .773 .216

N 50 50 50 50 50 50 50

x2 Pearson Correlation .417 ** -.125 1 .277 .256 -.095 -.205

Sig. (2-tailed) .003 .387 .052 .073 .513 .154

N 50 50 50 50 50 50 50

x3 Pearson Correlation .644 ** .078 .277 1 .933 ** -.119 -.224

Sig. (2-tailed) .000 .591 .052 .000 .409 .117

N 50 50 50 50 50 50 50

x4 Pearson Correlation .652 ** .108 .256 .933 ** 1 -.076 -.203

Sig. (2-tailed) .000 .455 .073 .000 .598 .158

N 50 50 50 50 50 50 50

x5 Pearson Correlation .042 -.042 -.095 -.119 -.076 1 .060

Sig. (2-tailed) .775 .773 .513 .409 .598 .680

N 50 50 50 50 50 50 50

x6 Pearson Correlation -.320 * .178 -.205 -.224 -.203 .060 1

Sig. (2-tailed) .023 .216 .154 .117 .158 .680

N 50 50 50 50 50 50 50

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

*. Correlation is significant at the 0.05 level (2-tailed).

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA/CRITERIA=PIN(.05) POUT(.10)/NOORIGIN/DEPENDENT y/METHOD=ENTER x1 x2 x3 x4 x5 x6.

Regression


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Notes

Output Created 17-Dec-2012 05:28:37

Comments

Input Active Dataset DataSet0

Filter

Weight

Split File

N of Rows in Working Data

File

50

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 y

/METHOD=ENTER x1 x2 x3 x4 x5 x6.

Resources Processor Time 0:00:00.016

Elapsed Time 0:00:00.031

Memory Required 3076 bytes

Additional Memory Required

for Residual Plots

0 bytes

[DataSet0]

Variables Entered/Removed b

Model

Variables

Entered

Variables

Removed Method

1 x6, x5, x1, x2, x4,

x3 a

. Enter

a. All requested variables entered.

b. Dependent Variable: y


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Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .732 a .536 .472 5.62562

a. Predictors: (Constant), x6, x5, x1, x2, x4, x3

ANOVA b

Model Sum of Squares df Mean Square F Sig.

1 Regression 1573.973 6 262.329 8.289 .000 a

Residual 1360.847 43 31.648

Total 2934.820 49

a. Predictors: (Constant), x6, x5, x1, x2, x4, x3


Coefficients a

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) -3.671 11.582 -.317 .753

x1 .005 .012 .046 .425 .673

x2 .021 .009 .250 2.267 .029

x3 .108 .147 .215 .735 .466

x4 .023 .018 .358 1.233 .224

x5 .002 .001 .130 1.232 .224

x6 -.119 .080 -.164 -1.496 .142

a. Dependent Variable: y

R 2 = 0.536

S = 5.62562

F= 8.289


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PARTIAL CORR/VARIABLES=y x2 x3 x4 x5 x6 BY x1/SIGNIFICANCE=TWOTAIL/MISSING=LISTWISE.

Partial Corr

Notes


Comments


Filter

Weight

Split File


File

50

Missing Value Handling Definition of Missing User defined missing values are treated

as missing.


missing data for any variable listed.

Syntax PARTIAL CORR

/VARIABLES=y x2 x3 x4 x5 x6 BY x1

/SIGNIFICANCE=TWOTAIL

/MISSING=LISTWISE.



[DataSet0]

Correlations

Control Variables y x2 x3 x4 x5 x6


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x1 y Correlation 1.000 .425 .643 .652 .043 -.332

Significance (2-tailed) . .002 .000 .000 .769 .020

df 0 47 47 47 47 47

x2 Correlation .425 1.000 .290 .273 -.101 -.187

Significance (2-tailed) .002 . .043 .058 .491 .198

df 47 0 47 47 47 47

x3 Correlation .643 .290 1.000 .932 -.117 -.243

Significance (2-tailed) .000 .043 . .000 .425 .093

df 47 47 0 47 47 47

x4 Correlation .652 .273 .932 1.000 -.072 -.227

Significance (2-tailed) .000 .058 .000 . .622 .117

df 47 47 47 0 47 47

x5 Correlation .043 -.101 -.117 -.072 1.000 .068

Significance (2-tailed) .769 .491 .425 .622 . .640

df 47 47 47 47 0 47

x6 Correlation -.332 -.187 -.243 -.227 .068 1.000

Significance (2-tailed) .020 .198 .093 .117 .640 .

df 47 47 47 47 47 0

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA/CRITERIA=PIN(.05) POUT(.10)/NOORIGIN/DEPENDENT y/METHOD=ENTER x2 x3 x4 x5 x6.

Regression

Notes


Comments



7/23

Filter

Weight

Split File


File

50


as missing.



Syntax REGRESSION

/MISSING LISTWISE



/NOORIGIN

/DEPENDENT y

/METHOD=ENTER x2 x3 x4 x5 x6.





for Residual Plots

0 bytes

[DataSet0]


Model

Variables

Entered

Variables

Removed Method

1 x6, x5, x4, x2, x3 a . Enter



Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate


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Notes


Comments


Filter

Weight

Split File


File

50


as missing.



Syntax PARTIAL CORR

/VARIABLES=y x2 x3 x4 x6 BY x1 x5


/MISSING=LISTWISE.



[DataSet0]

Correlations

Control Variables y x2 x3 x4 x6

x1 & x5 y Correlation 1.000 .432 .654 .657 -.336

Significance (2-tailed) . .002 .000 .000 .019

df 0 46 46 46 46

x2 Correlation .432 1.000 .281 .268 -.181

Significance (2-tailed) .002 . .053 .066 .217

df 46 0 46 46 46

x3 Correlation .654 .281 1.000 .933 -.237


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Significance (2-tailed) .000 .053 . .000 .105

df 46 46 0 46 46

x4 Correlation .657 .268 .933 1.000 -.223

Significance (2-tailed) .000 .066 .000 . .128

df 46 46 46 0 46

x6 Correlation -.336 -.181 -.237 -.223 1.000

Significance (2-tailed) .019 .217 .105 .128 .

df 46 46 46 46 0

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)/NOORIGIN/DEPENDENT y/METHOD=ENTER x2 x3 x4 x6.

Regression

Notes


Comments


Filter

Weight

Split File


File

50


as missing.




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Syntax REGRESSION

/MISSING LISTWISE



/NOORIGIN

/DEPENDENT y

/METHOD=ENTER x2 x3 x4 x6.





for Residual Plots

0 bytes

[DataSet0]


Model

Variables

Entered

Variables

Removed Method

1 x6, x4, x2, x3 a . Enter



Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .720 a .519 .476 5.60332

a. Predictors: (Constant), x6, x4, x2, x3

ANOVA b


1 Regression 1521.947 4 380.487 12.119 .000 a

Residual 1412.873 45 31.397


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Total 2934.820 49

a. Predictors: (Constant), x6, x4, x2, x3


Coefficients a

Model


Standardized

Coefficients


1 (Constant) 2.119 7.291 .291 .773

x2 .020 .009 .236 2.170 .035

x3 .084 .145 .166 .575 .568

x4 .025 .018 .405 1.413 .164

x6 -.111 .078 -.153 -1.421 .162


R 2 = 0.519

S = 5.60332

F = 12.119

PARTIAL CORR/VARIABLES=y x2 x3 x4 BY x1 x5 x6/SIGNIFICANCE=TWOTAIL/MISSING=LISTWISE.

Partial Corr

Notes


Comments


Filter

Weight

Split File


13/23


File

50


as missing.

Cases Used Statistics are based on cases with nomissing data for any variable listed.

Syntax PARTIAL CORR

/VARIABLES=y x2 x3 x4 BY x1 x5 x6


/MISSING=LISTWISE.



[DataSet0]

Correlations

Control Variables y x2 x3 x4

x1 & x5 & x6 y Correlation 1.000 .401 .627 .634

Significance (2-tailed) . .005 .000 .000df 0 45 45 45

x2 Correlation .401 1.000 .249 .237

Significance (2-tailed) .005 . .091 .109

df 45 0 45 45

x3 Correlation .627 .249 1.000 .929

Significance (2-tailed) .000 .091 . .000

df 45 45 0 45

x4 Correlation .634 .237 .929 1.000

Significance (2-tailed) .000 .109 .000 .

df 45 45 45 0

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA/CRITERIA=PIN(.05) POUT(.10)


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/NOORIGIN/DEPENDENT y/METHOD=ENTER x2 x3 x4.

Regression

Notes


Comments


Filter Weight

Split File


File

50


as missing.



Syntax REGRESSION/MISSING LISTWISE



/NOORIGIN

/DEPENDENT y

/METHOD=ENTER x2 x3 x4.





for Residual Plots

0 bytes

[DataSet0]


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R 2 = 0.497

S = 5.66506

F = 15.149

PARTIAL CORR/VARIABLES=y x3 x4 BY x1 x5 x6 x2/SIGNIFICANCE=TWOTAIL/MISSING=LISTWISE.

Partial Corr

Notes


Comments


Filter

Weight

Split File


File

50


as missing.



Syntax PARTIAL CORR

/VARIABLES=y x3 x4 BY x1 x5 x6 x2

/SIGNIFICANCE=TWOTAIL/MISSING=LISTWISE.



[DataSet0]


17/23

Correlations

Control Variables y x3 x4

x1 & x5 & x6 & x2 y Correlation 1.000 .594 .606

Significance (2-tailed) . .000 .000

df 0 44 44

x3 Correlation .594 1.000 .925

Significance (2-tailed) .000 . .000

df 44 0 44

x4 Correlation .606 .925 1.000

Significance (2-tailed) .000 .000 .

df 44 44 0

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA/CRITERIA=PIN(.05) POUT(.10)/NOORIGIN/DEPENDENT y/METHOD=ENTER x3 x4.

Regression

Notes


Comments


Filter

Weight

Split File


File

50


18/23


as missing.



Syntax REGRESSION/MISSING LISTWISE



/NOORIGIN

/DEPENDENT y

/METHOD=ENTER x3 x4.





for Residual Plots

0 bytes

[DataSet0]


Model

Variables

Entered

Variables

Removed Method

1 x4, x3 a . Enter



Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .659 a .435 .411 5.94182

a. Predictors: (Constant), x4, x3


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ANOVA b


1 Regression 1275.476 2 637.738 18.064 .000 a

Residual 1659.344 47 35.305

Total 2934.820 49

a. Predictors: (Constant), x4, x3


Coefficients a

Model


Standardized

Coefficients


1 (Constant) 6.520 1.712 3.808 .000

x3 .139 .153 .278 .913 .366

x4 .025 .019 .393 1.292 .203


R 2 = 0.435

S = 5.94182

F = 18.064

PARTIAL CORR/VARIABLES=y x4 BY x1 x5 x6 x2 x3/SIGNIFICANCE=TWOTAIL/MISSING=LISTWISE.

Partial Corr

Notes


Comments


Filter


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Weight

Split File


File

50

Missing Value Handling Definition of Missing User defined missing values are treatedas missing.



Syntax PARTIAL CORR

/VARIABLES=y x4 BY x1 x5 x6 x2 x3


/MISSING=LISTWISE.



[DataSet0]

Correlations

Control Variables y x4

x1 & x5 & x6 & x2 & x3 y Correlation 1.000 .185

Significance (2-tailed) . .224

df 0 43

x4 Correlation .185 1.000

Significance (2-tailed) .224 .

df 43 0

REGRESSION/MISSING LISTWISE/STATISTICS COEFF OUTS R ANOVA/CRITERIA=PIN(.05) POUT(.10)/NOORIGIN/DEPENDENT y/METHOD=ENTER x4.


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Regression

Notes Output Created 17-Dec-2012 05:33:55

Comments


Filter

Weight

Split File


File

50


as missing.



Syntax REGRESSION

/MISSING LISTWISE



/NOORIGIN

/DEPENDENT y/METHOD=ENTER x4.





for Residual Plots

0 bytes

[DataSet0]


Model

Variables

Entered

Variables

Removed Method


22/23

1 x4 a . Enter



Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .652 a .425 .413 5.93152

a. Predictors: (Constant), x4

ANOVA b


1 Regression 1246.039 1 1246.039 35.416 .000 a

Residual 1688.781 48 35.183

Total 2934.820 49

a. Predictors: (Constant), x4


Coefficients a

Model


Standardized

Coefficients


1 (Constant) 5.965 1.598 3.733 .001

x4 .041 .007 .652 5.951 .000


R = 0.425

S = 5.93152

F = 35.416

Jadi, persamaan regresi terbaiknya adalah


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