Uji Regression untuk pengaruh satu tahun kedepan (1)

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Uji Regression untuk pengaruh satu tahun kedepan (1)

Variables Entered/Removeda

INWC .

Stepwise (Criteria: Probabilit y-of-F-to-e nter <= .050, Probabilit y-of-F-to-r emove >= .100). nter <= .050, Probabilit y-of-F-to-r emove >= .100). nter <= .050, Probabilit y-of-F-to-r emove >= .100).

Removed Method

Dependent Variable: LABA01 a.

Model Summaryd

.277a _.077 _.066 _1.41679

.345b _.119 _.098 _1.39240

.399c .159 .129 1.36801 1.842

Model R Square

Std. Error of the Estimate

Durbin-W atson

Predictors: (Constant), INWC a.

Predictors: (Constant), INWC, STA b.

Predictors: (Constant), INWC, STA, CFCL c.

Dependent Variable: LABA01 d.

(4)

ANOVA

d

14.373

1

14.373

7.161 .009

a

172.626

86

2.007

186.999

87

22.202

2

11.101

5.726 .005

b

164.797

85

1.939

186.999

87

29.797

3

9.932

5.307 .002

c

157.202

84

1.871

186.999

87 Regression

Squares

df

Mean Square

F

Sig.

Predictors: (Constant), INWC

a.

Predictors: (Constant), INWC, STA

b.

Predictors: (Constant), INWC, STA, CFCL

c.

Dependent Variable: LABA01

d.

Coefficientsa

.126 .158 .795 .429

-.374 .140 -.277 -2.676 .009 1.000 1.000

.134 .155 .865 .390

-.455 .143 -.338 -3.180 .002 .920 1.087

-1.188 .591 -.213 -2.010 .048 .920 1.087

.162 .153 1.054 .295

-.517 .144 -.384 -3.595 .001 .877 1.140

-1.185 .581 -.213 -2.039 .045 .920 1.087

-.378 .188 -.207 -2.014 .047 .949 1.053

(Constant)

B Std. Error Unstandardized

Coefficients

Beta Standardized

Coefficients

t Sig. Tolerance VIF

Collinearity Statistics

(5)

Excluded Variablesd

-.042a _-.390 _.698 _-.042 _.946 _1.057 _.946 -.168a _-1.639 _.105 _-.175 _.997 _1.003 _.997 -.094a _-.903 _.369 _-.097 _.999 _1.001 _.999 .042a _.387 _.700 _.042 _.935 _1.069 _.935 -.125a _-1.185 _.239 _-.127 _.966 _1.035 _.966 -.185a _-1.634 _.106 _-.174 _.817 _1.224 _.817 -.095a _-.875 _.384 _-.094 _.911 _1.098 _.911 -.144a _-1.382 _.171 _-.148 _.978 _1.022 _.978 -.207a _-1.984 _.050 _-.210 _.949 _1.053 _.949 .065a _.596 _.553 _.065 _.905 _1.105 _.905 -.213a _-2.010 _.048 _-.213 _.920 _1.087 _.920 -.078a _-.746 _.458 _-.081 _.977 _1.023 _.977 .076a _.729 _.468 _.079 _.988 _1.013 _.988 -.092a _-.865 _.390 _-.093 _.955 _1.047 _.955 -.011a _-.100 _.920 _-.011 _.963 _1.039 _.963 -.202a _-1.949 _.055 _-.207 _.963 _1.038 _.963 -.158a _-1.522 _.132 _-.163 _.982 _1.018 _.982 -.044b _-.414 _.680 _-.045 _.946 _1.057 _.875 -.128b _-1.230 _.222 _-.133 _.945 _1.058 _.872 -.110b _-1.080 _.283 _-.117 _.993 _1.007 _.914 .022b _.205 _.838 _.022 _.927 _1.079 _.875 -.077b _-.716 _.476 _-.078 _.904 _1.106 _.861 -.161b _-1.426 _.158 _-.154 _.806 _1.241 _.780 -.074b _-.685 _.495 _-.075 _.901 _1.109 _.857 -.156b _-1.527 _.130 _-.164 _.975 _1.025 _.897 -.207b -2.014 .047 -.215 .949 1.053 .877 .074b _.686 _.495 _.075 _.904 _1.106 _.834 -.133b _-1.258 _.212 _-.136 _.926 _1.080 _.872 -.045b _-.374 _.710 _-.041 _.711 _1.406 _.663 -.171b _-1.577 _.119 _-.170 _.868 _1.152 _.835 -.007b _-.062 _.950 _-.007 _.963 _1.039 _.890 -.189b _-1.844 _.069 _-.197 _.959 _1.043 _.882 -.130b _-1.254 _.213 _-.136 _.960 _1.042 _.899 -.052c _-.499 _.619 _-.055 _.944 _1.059 _.839 .119c _1.108 _.271 _.121 _.871 _1.148 _.776 -.074c _-.674 _.502 _-.074 _.834 _1.198 _.834 -.048c _-.405 _.687 _-.044 _.711 _1.406 _.663 -.142c _-1.312 _.193 _-.143 _.849 _1.178 _.834 -.016c _-.154 _.878 _-.017 _.961 _1.041 _.847 -.166c _-1.629 _.107 _-.176 _.944 _1.059 _.833 -.134c _-1.313 _.193 _-.143 _.960 _1.042 _.870 TLTA

Correlation Tolerance VIF

Minimum Tolerance Collinearity Statistics

Predictors in the Model: (Constant), INWC a.

Predictors in the Model: (Constant), INWC, STA b.

Predictors in the Model: (Constant), INWC, STA, CFCL c.

Dependent Variable: LABA01 d.

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Coefficient Correlations

a

1.000 1.949E-02

1.000 .283

.283

1.000 2.046E-02

2.395E-02

.350

1.000 .276

.215

.276

1.000 -.003

.215

-.003

1.000 2.071E-02

2.306E-02

5.815E-03

2.306E-02

.338

-3.21E-04

5.815E-03

-3.21E-04

3.525E-02

INWC

STA

CFCL

Dependent Variable: LABA01

a.

Collinearity Diagnostics

a

1.294

1.000 .35

.35

.706

1.354 .65

.65

Index

(Constant)

INWC

STA

CFCL

Variance Proportions

Dependent Variable: LABA01

a.

Casewise Diagnostics

a

3.445

5.58

7.163

12.05 Case Number

74

79 Std. Residual

LABA01

Dependent Variable: LABA01

a.

(7)

Residuals Statisticsa

-1.4254 2.2537 .2499 .58523 88

-2.863 3.424 .000 1.000 88

.14743 .76497 .26671 .11870 88

-1.7022 1.5199 .2199 .59903 88

-1.6901 9.7990 .0000 1.34422 88

-1.235 7.163 .000 .983 88

-1.280 7.785 .010 1.047 88

-1.8142 11.5760 .0300 1.53027 88

-1.285 14.666 .092 1.699 88

.022 26.215 2.966 4.231 88

.000 2.748 .038 .293 88

.000 .301 .034 .049 88

Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual

Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Mahal. Distance Cook's Distance Centered Leverage Value

Minimum Maximum Mean Std. Deviation N

Charts

Normal P-P Plot of Regression Standardized Residual

Dependent Variable: LABA01

Observed Cum Prob

1.00 .75 .50 .25 0.00

Expected Cum Prob

1.00

.75

.50

.25

(8)

Scatterplot

Dependent Variable: LABA01

Regression Standardized Residual

8 6

4 2

0 -2

Regression Studentized Residual

8

6

4

2

0

-2

NPar Tests

One-Sample Kolmogorov-Smirnov Test

88 .0000000

1.34421861

.200

-.199

1.880 .002

N

Mean

Std. Deviation

Normal Parameters

a,b

Absolute

Positive

Negative

Most Extreme

Differences

Kolmogorov-Smirnov Z

Asymp. Sig. (2-tailed)

Unstandardiz

ed Residual

Test distribution is Normal.

a.

Calculated from data.

b.

(9)

Regression (2)

Variables Entered/Removeda

ROA .

Stepwise (Criteria: Probabilit y-of-F-to-e nter <= .050, Probabilit y-of-F-to-r emove >= .100). nter <= .050, Probabilit y-of-F-to-r emove >= .100).

Removed Method

Model Summaryc

.298a _.089 _.078 _.41459

.460b _.212 _.193 _.38787 _1.375

Model 1 2

R R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-W atson

Predictors: (Constant), ROA a.

Predictors: (Constant), ROA, ROE b.

Dependent Variable: LABA01 c.

ANOVA

c

1.408

1

1.408

8.193 .005

a

14.439

84 .172

15.847

85

3.360

2

1.680

11.166 .000

b

12.487

83 .150

15.847

85 Regression

Squares

df

Mean Square

F

Sig.

Predictors: (Constant), ROA

a.

Predictors: (Constant), ROA, ROE

b.

Dependent Variable: LABA01

c.

(10)

Coefficientsa

6.833E-02 .045 1.514 .134

.242 .084 .298 2.862 .005 1.000 1.000

6.227E-02 .042 1.474 .144

.377 .088 .465 4.312 .000 .815 1.227

-.365 .101 -.389 -3.602 .001 .815 1.227

(Constant)

B Std. Error Unstandardized

Coefficients

Beta Standardized

Coefficients

t Sig. Tolerance VIF

Collinearity Statistics

Excluded Variablesc

.065a _.619 _.538 _.068 _.997 _1.003 _.997

-.035a -.336 .738 -.037 .986 1.015 .986 -.150a _-1.453 _.150 _-.157 _.999 _1.001 _.999

-.008a _-.071 _.943 _-.008 _.984 _1.017 _.984

-.020a _-.188 _.851 _-.021 _.984 _1.017 _.984

.009a _.082 _.935 _.009 _.999 _1.001 _.999

-.081a _-.765 _.446 _-.084 _.984 _1.016 _.984

-.155a _-1.495 _.139 _-.162 _.998 _1.002 _.998

-.144a -1.387 .169 -.151 1.000 1.000 1.000 -.153a _-1.473 _.144 _-.160 _.998 _1.002 _.998

.010a _.094 _.926 _.010 _.995 _1.005 _.995

.012a _.112 _.911 _.012 _.954 _1.048 _.954

-.136a _-1.306 _.195 _-.142 _.991 _1.009 _.991

.108a _1.006 _.317 _.110 _.945 _1.058 _.945

-.182a _-1.511 _.134 _-.164 _.739 _1.352 _.739

-.389a _-3.602 _.001 _-.368 _.815 _1.227 _.815

-.016a _-.154 _.878 _-.017 _.977 _1.023 _.977

.131b _1.324 _.189 _.145 _.967 _1.035 _.790

-.004b _-.037 _.971 _-.004 _.978 _1.023 _.808

-.181b _-1.879 _.064 _-.203 _.992 _1.008 _.809

.078b _.771 _.443 _.085 _.932 _1.073 _.772

-.008b _-.082 _.935 _-.009 _.982 _1.018 _.806

-.055b _-.550 _.583 _-.061 _.969 _1.032 _.790

-.112b _-1.133 _.260 _-.124 _.977 _1.024 _.796

-.136b _-1.401 _.165 _-.153 _.995 _1.005 _.812

-.123b _-1.262 _.211 _-.138 _.996 _1.004 _.812

-.110b _-1.115 _.268 _-.122 _.981 _1.019 _.801

-.009b _-.087 _.931 _-.010 _.993 _1.007 _.809

.120b _1.163 _.248 _.127 _.881 _1.135 _.735

-.134b _-1.374 _.173 _-.150 _.991 _1.009 _.809

.026b _.250 _.803 _.028 _.895 _1.118 _.737

Correlation Tolerance VIF

Minimum Tolerance Collinearity Statistics

Predictors in the Model: (Constant), ROA a.

Predictors in the Model: (Constant), ROA, ROE b.

Dependent Variable: LABA01 c.

(11)

Coefficient Correlations

a

1.000 7.132E-03

1.000 -.430

-.430

1.000 7.662E-03

-3.82E-03

1.029E-02

ROA

ROE

ROA

ROE

Correlations

Covariances

Correlations

Covariances

Model

1

2 ROA

ROE

Dependent Variable: LABA01

a.

Collinearity Diagnostics

a

1.137

1.000 .43

.43

.863

1.148 .57

.57

1.492

1.000 .07

.25

.24

.947

1.255 .93

.03

.06

.560

1.632 .01

.73

.70

Dimension

1

2

1

2

3 Model

1

2 Eigenvalue

Condition

Index

(Constant)

ROA

ROE

Variance Proportions

Dependent Variable: LABA01

a.

Casewise Diagnosticsa

3.424 1.41 3.147 1.12 Case Number

68 76

Std. Residual LABA01

(12)

Residuals Statistics

a

-.4593

1.3127

.0507

.19882

86 -2.565

6.348 .000

1.000

86 .04184

.30201

.06327

.03549

86 -.4925

1.8346

.0555

.24171

86 -.9806

1.3280

.0000

.38328

86 -2.528

3.424 .000

.988

86 -2.558

3.478 -.005

1.008

86 -1.0040

1.3704

-.0049

.40285

86 -2.649

3.740 .000

1.037

86 .001

50.546

1.977

5.889

86 .000

.995

.021

.108

86 .000

.595

.023

.069

86 Predicted Value

Std. Predicted Value

Standard Error of

Predicted Value

Adjusted Predicted Value

Residual

Std. Residual

Stud. Residual

Deleted Residual

Stud. Deleted Residual

Mahal. Distance

Cook's Distance

Centered Leverage Value

Minimum

Maximum

Mean

Std. Deviation

N

Dependent Variable: LABA01

a.

Charts

Normal P-P Plot of Regression Standardized Residual

Dependent Variable: LABA01

Observed Cum Prob

1.00 .75 .50 .25 0.00

Expected Cum Prob

1.00

.75

.50

.25

0.00

(13)

Scatterplot

Dependent Variable: LABA01

Regression Standardized Residual

4 3 2 1 0 -1 -2 -3

Regression Studentized Residual

4 3 2 1 0 -1 -2 -3

NPar Tests

One-Sample Kolmogorov-Smirnov Test

86 .0000000

.38328353

.120

-.095

1.116 .166

N

Mean

Std. Deviation

Normal Parameters

a,b

Absolute

Positive

Negative

Most Extreme

Differences

Kolmogorov-Smirnov Z

Asymp. Sig. (2-tailed)

Unstandardiz

ed Residual

Test distribution is Normal.

a.

Calculated from data.

b.

(14)

Uji Heteroskedastisitas untuk pengaruh satu tahun kedepan

Variables Entered/Removedb

ROE, ROAa _. _Enter

Model 1

Variables Entered

Variables

Removed Method

All requested variables entered. a.

Dependent Variable: H b.

Model Summary

.182

a

_.033

_.010

_.27359

Model

1 R

R Square

Adjusted

R Square

Std. Error of

the Estimate

Predictors: (Constant), ROE, ROA

a.

ANOVAb

.214 2 .107 1.428 .246a

6.213 83 .075

6.427 85

Regression Residual Total Model 1

Sum of

Squares df Mean Square F Sig.

Predictors: (Constant), ROE, ROA a.

Dependent Variable: H b.

Coefficients

a

.260

.030

8.738 .000

-4.70E-03

.062

-.009

-.076

.940

.815

1.227 -.107

.072

-.178

-1.491

.140

.815

1.227 (Constant)

ROA

ROE

Model

1 B

Std. Error

Unstandardized

Coefficients

Beta

Standardized

Coefficients

t

Sig.

Tolerance

VIF

Collinearity Statistics

Dependent Variable: H

a.

(15)

Coefficient Correlationsa

1.000 -.430 -.430 1.000 5.121E-03 -1.90E-03 -1.90E-03 3.812E-03 ROE

ROA ROE ROA Correlations

Covariances Model

1

ROE ROA

Dependent Variable: H a.

Collinearity Diagnosticsa

1.492 1.000 .07 .25 .24

.947 1.255 .93 .03 .06

.560 1.632 .01 .73 .70

Dimension 1 2 3 Model 1

Eigenvalue

Condition

Index (Constant) ROA ROE

Variance Proportions

Dependent Variable: H a.

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Uji Regression untuk pengaruh dua tahun kedepan

Variables Entered/Removed

a