ANNEXES
Plan des annexes :
Annexe 1 : Estimation par la
méthode des MCO de la régression 1 de la relation entre la
sous-évaluation et le taux des actions retenues.
Annexes 2 : Estimation par la
méthode des MCO de la régression 2 de la relation entre la
sous-évaluation et le taux des actions retenues.
Annexes 3 : Estimation par la
méthode des MCO de la régression 3 de la relation entre la
sous-évaluation et le taux des actions retenues.
Annexes 4 : Estimation par la
méthode des MCO de la régression 4 de la relation entre la
sous-évaluation et la taux des actions retenues.
Annexes 5 : Estimation par la
méthode des MCO de la régression 5 de la relation entre la
sous-évaluation et le taux des actions retenues.
Annexes 6 : Estimation par la
méthode des MCO de la régression 1 de la relation entre la
liquidité et la sous-évaluation initiale.
Annexes 7 : Tableau de
corrélations des variables de la régression 1 de la relation
entre la liquidité et la sous-évaluation initiale.
Annexes 8 : Estimation par la
méthode des MCO de la régression 2 de la relation entre la
liquidité et la sous-évaluation initiale.
Annexes 9 : Tableau de
corrélations des variables de la régression 2 de la relation
entre la liquidité et la sous-évaluation initiale.
Annexes 10 : Estimation par la
méthode des MCO de la régression 3 de la relation entre la
liquidité et la sous-évaluation initiale.
Annexes 11 : Tableau de
corrélations des variables de la régression 3 de la relation
entre la liquidité et la sous-évaluation initiale.
Annexe.1 : Estimation par la méthode MCO de
la régression 1 du modèle.1.
Coefficientsa
Modèle
|
Coefficients non standardisés
|
Coefficients
standardisés
|
t
|
Signification
|
B
|
Erreur
standard
|
Bêta
|
1 (constante) Retention1
LAG
RUNUP
|
-,431
,770
-1,037
-,313
|
,528
,687
6,157
,575
|
,195
-,029
-,094
|
-,816
1,121
-,168
-,544
|
,420
270
,867
,590
|
a. Variable dépendante: RI
Récapitulatif du
modèleb
Modèle
|
R
|
R-deux
|
R-deux ajusté
|
Durbin-W
atson
|
1
|
,195a
|
,038
|
-,047
|
2,009
|
a. Valeurs prédites : (constantes), Runup, LAG,
Retention1
b.Variable dépendante : RI
ANOVAb
Modèle
|
Somme
des carrés
|
ddl
|
Carré moyen
|
F
|
Signification
|
1 Régression
Résidu
Total
|
,230
5,808
6,039
|
3
34
37
|
,077
,171
|
,449
|
,720a
|
a. Valeurs prédites : (constantes), Runup, LAG,
Retention1
b. Variable dépendante : RI
Corrélations
|
RI
|
Retention 1
|
LAG
|
RUNUP
|
Corrélation de Pearson RI
Retention1
LAG
RUNUP
|
1,000
,171
-,004-
-,050
|
,171
1,000
,104
,218
|
-,004
,104
1,000
-,049_
|
-,050
,218
-,049
1,000
|
Signification (unilatérale) RI
Retention1
LAG
RUNUP
|
,
,152
,491
,382
|
,152
,
,267
,095
|
,491
,267
,
,385
|
,382
,095
, 385
,
|
N RI
Retention1
LAG
RUNUP
|
38
38
38
38
|
38
38
38
38
|
38
38
38
38
|
38
38
38
38
|
Annexe.2 : Estimation par la méthode
MCO de la régression 2 du modèle.1.
Coefficients a
Modèle
|
Coefficients non
standardisés
|
Coefficients
standardisés
|
t
|
Signification
|
B
|
Erreur
standard
|
Bêta
|
1 (constante)
Retention1
LAG
UWMS
LN
|
-3,519
1,346
-1,125
,195
,157
|
1,524
,786
5,940
,891
,076
|
,340
-,031
,039
,384
|
-2,309
1,713
-,189
,219
2,063
|
,027
,096
,851
,828
,047
|
a. Variable dépendante: RI
ANOVA
Modèle
|
Somme
des carrés
|
ddl
|
Carré moyen
|
F
|
Signification
|
1 Régression
Résidu
Total
|
,917
5,121
6,039
|
4
33
37
|
,229
,155
|
1,478
|
,231
|
Récapitulatif du
modèle
Modèle
|
R
|
R-deux
|
R-deux ajusté
|
Durbin-W
atson
|
1
|
,390
|
,152
|
,049
|
,008
|
Corrélations
|
RI
|
Retention1
|
LAG
|
UWMS
|
LN
|
Corrélation de Pearson RI
Retention1
LAG
UWMS
LN
|
1,000
,171
-,004
,164
,227
|
,171
1,000
,104
,323
-,465
|
-,004
,104
1,000
-,109
-,010
|
,164
,323
-,109
1,000
,032
|
,227
-,465
-,010
,032
1,000
|
Signification(unilatérale) RI
Retention1
LAG
UWMS
LN
|
,
,152
,491
,163
,085
|
,152
,
,267
,024
,002
|
,491
,267
,,258
,475
|
,163
,024
,258
,
,424
|
,085
,002
,475
,424
,
|
N RI
Retention1
LAG
UWMS
LN
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
Annexe.3: Estimation par la méthode MCO de
la régression 3 du modèle.1.
Coefficients a
Modèle
|
Coefficients non
standardisés
|
Coefficients
standardisés
|
t
|
Signification
|
B
|
Erreur `
standard
|
Bêta
|
1 (constante)
Retntion1 RUNUP UWMS LISIZE
|
-,981
,668
-,268
,595
1,386
|
1,720
,849
,587
,912
,092
|
,169
-,080
,117
,032
|
-,570
,787
-,456
,652
,151
|
,572
,437
,651
,519
,881
|
a. Variable dépendante: RI
AN OVA
Modèle
|
Somme
des carrés
|
ddl
|
Carré moyen
|
F
|
Signification
|
1 Régression
Résidu
Total
|
,301
5,737
6,039
|
4
33
37
|
,075
,174
|
,434
|
,783
|
Récapitulatif du modèle
Modèle
|
R
|
R-deux
|
R-deux ajusté
|
Durbin-W
atson
|
1
|
,223
|
,050
|
-,065
|
2,013
|
Corrélations
|
RI
|
Retention1
|
RUNUP
|
UWMS
|
LISIZE
|
Corrélation dePearson RI
Retention1
RUNUP
UWMS
LISIZE
|
1,000
,171
-,050
,164
-,071
|
,171
1,000
,218
,323
-,571
|
-,050
,218
1,000
,010
-,244
|
,164
,323
,010
1,000
-,224
|
,071
-,571
-,244
-,224
1,000
|
Signification (unilatérale) RI
Retention1
RUNUP
UWMS
LISIZE
|
,
,152
,382
,163
,335
|
152
,
,095
,024
,000
|
,382
,095
,
,476
,070
|
,163
,024
,476
,
,089
|
,335
,000
,070
,089
,
|
N RI
Retention1
RUNUP
UWMS
LISIZE
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38
38
|
Annexe.4: Estimation par la méthode MCO de
la régression 4 du modèle.1.
Coefficients
a
Modèle
|
Coefficients non standardisés
|
Coefficien standardisés
s
|
t
|
Signification
|
B
|
Erreur
standard
|
Bêta
|
1 (constante)
Retention1
LISIZE
INVP
LN
|
-4,022
,373
-1,024
14,474
1,018
|
1,103
,513
,155
2,534
,139
|
,094
-2,338
1,172
2,482
|
-3,647
,728
-6,587
5,712
7,312
|
,001
,472
,000
,000
,000
|
a. Variable dépendante: RI
ANOVA
Modèle
|
Somme des carrés
|
ddl
|
Carré moyen
|
F
|
Signification
|
1 Régression
Résidu
Total
|
3,824
2,215
6,039
|
4
33
37
|
,956
,067
|
14,244
|
,000
|
Récapitulatif du
modèle
Modèle
|
R
|
R-deux
|
R-deux ajusté
|
Durbin-W
atson
|
1
|
,796
|
,633
|
,589
|
2,346
|
Corrélations
|
RI
|
Retention1
|
LISIZE
|
INVP
|
LN
|
Corrélation de Pearson RI
Retention1
LISIZE
INVP
LN
|
1,000
,171
-,071
-,098
,227
|
,171
1,000
-,571
-,091
-,465
|
-,071
-,571
1,000
,259
,813
|
-,098
-,091
,259
1,000
-,264
|
,227
-,465
,813
-,264
1,000
|
Signification (unilatérale) RI
Retention1
LISIZE
INVP
LN
|
,
,152
,335
,280.
,085
|
,152
,
,000
,293
,002
|
,335
,000
,
,058
,000
|
,280
,293
,058
,
,054
|
,085
,002
,000
,054
,
|
N RI
Retention1
LISIZE
INVP
LN
|
38
38
38
38
38
|
38
38
38
38
38
|
38
38
38
38 38
|
38
38
38
38
38
|
38
38
38
38
38
|
Annexe.5: Estimation par la méthode MCO de
la régression 5 du modèle.1.
Coefficientsa
Modèle
|
Coefficients non
standardisés
|
Coefficients
standardisés
|
t
|
Signification
|
B
|
Erreur standard
|
Bêta
|
1 (constante)
Retention1
LAG
RUNUP
UWMS
LISIZE
INVP
LN
|
-5,053
1,403E-02
-7,217
3,809E-02
1,378
-1,167
18,249
1,140
|
1,092
,505
3,661
,336
,640
,149
2,652
,133
|
,004
-,199
,011
,272
-2,666
1,477
2,779
|
-4,629
,028
-1,971
,113
2,153
-7,840
6,882
8,545
|
,000
,978
,058
,910
,039
000
,000
,000
|
a. Variable dépendante: RI
ANOVA
Modèle
|
Somme
des carrés
|
ddl
|
Carré moyen
|
F
|
Signification
|
1 Régression
Résidu
Total
|
4,370
1,669
6,039
|
7
30
37
|
,624
,056
|
11,220
|
,000
|
Récapitulatif du
modèle
Modèle
|
R
|
R-deux
|
R-deux ajusté
|
Durbin-W
atson
|
1
|
,851
|
,724
|
,659
|
2,190
|
Corrélation
|
RI
|
Retention1
|
LAG
|
RUNUP
|
UWMS
|
LISIZE
|
INVP
|
Corrélation de Pearson RI
Retention1
LAG
RUNUP
UWMS
LISIZE
INVP
LN
|
1,000
,171
-,004
-,050
,164
-,071
-,098
,227
|
,171
1,000
,104
,218
,323
-,571
-,091
-,465
|
-,004
,104
1,000
-,049
-,109
-,093
,003
-,010
|
-,050
,218
-,049
1,000
,010
-,244
,019
-,271
|
,164
,323
-,109
,010
1,000
-,224
-,552
,032
|
-,071
,571
-,093
-,244
-,244
1,000
,259
,813
|
-,098
-,91
,003
,019
-,552
,259
1,000
-,264
|
Signification (unilatérale) RI
Retention1
LAG
RUNUP
UWMS
LISIZE
INVP
LN
|
,
,152
,491
,382
,163
,335
,280
,085
|
,152
,
,267
,095
,024
,000
,293
,002
|
,491
,267
,385
,258
,288
,493
,475
|
,382
,095
,385
,
,476
,070
,455
,050
|
,163
,024
,258
,476
,
,089
,000
,424
|
,335
,000
,288
,070
,089
,
,058
,000
|
,280
,293
,493
,455
,000
,058
,
,054
|
Annexe.6. Tableau de corrélations des
variables de la régression 1 du modèle.2.
Coefficients a
Model
|
Unstandardized
Coefficients
|
Standardi
zed
Coefficien
ts
|
t
|
Sig.
|
B
|
Std. Error
|
Beta
|
1 (Constant)
log RI
LAG
RUNP
RETENTION1
LISIZE
UWMS
INVP
LN
|
87,592
1,205
471,164
5,889
-18,882
-7,039
-13,303
31,247
1,921
|
40,453
,795
150,817
10,811
20,407
2,517
26,029
58,752
2,178
|
,210
,450
,074
-,167
-,564
-,080
,089
,159
|
2,165
1,516
3,124
,545
-,925
-2,796
-,511
,532
,882
|
,039
,140
,004
,590
362
,009
,613
,599
,385
|
a. Dependent Variable: moy volume transaction j1-j125.
ANOVAb
Model
|
Sum of
Squares
|
df
|
Mean
Square
|
F
|
Sig.
|
1 Regression
Residual
Total
|
2637,756
2274,070
4911,826
|
8
29
37
|
329,720
78,416
|
4,205
|
002a
|
a. Predictors: (Constant), LN, RETENTION1, LAG, RUNP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume transaction
j1-j125.
Model Summaryb
Model
|
R
|
R Square
|
Adjusted R Square
|
Std .Error of the Estimate
|
Durbin -W
atson
|
1
|
,733a
|
,537
|
,409
|
8,8553
|
1,110
|
a. Predictors: (Constant), LN, RETENTION1, LAG, RUNP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume transaction j1-j125.
Annexe.7. Tableau de corrélations des
variables de la régression 1 du modèle.2.
Correlations
|
log RI
|
LLAG
|
RUNUP
|
RETENTI
ON1
|
LLISIZE
|
UUWMS
|
INVP
|
L
L LN
|
Moy de volume de
Transaction
J1-j125
|
log RI Pearson Correlation
Sig. (2-tailed)
N
|
1,000
,
38
|
,164
,325
38
|
-,111
,509
38
|
-,291
,076
38
|
,132
,429
38
|
-.057
,733
38
|
,084
,618
38
|
,140
,401
38
|
,284
,084
38
|
LAG Pearson Correlation
Sig. (2-tailed)
N
|
,164
,325
38
|
1,000
,
38
|
-,051
,763
38
|
-,023
,891
38
|
,060
,722
38
|
-,387*
,016
38
|
105
',529
38
|
,219
,187
38
|
,525**
,001
38
|
RUNP Pearson Correlation
Sig. (2-tailed)
N
|
-,111
,509
38
|
-,051
,763
38
|
1,000
,
38
|
,210
,206
38
|
-,242
,144
38
|
-,197
,236
38
|
,016
,925
38
|
-,090
,591
38
|
,132
,428
38
|
RETENTION Pearson Correlation
Sig. (2-tailed)
N
|
-,291
,076
38
|
-,023
,891
38
|
,210
,206
38
|
1,000
,
38
|
-,571**
,000
38
|
,188
,259
38
|
-,091
,586
38
|
-,074
,658
38
|
,064
,702
38
|
LISIZE Pearson Correlation
Sig. (2-tailed)
N
|
,132
,429
38
|
,060
,722
38
|
-,242
,144
38
|
-,571
,000
38
|
1,000
,
38
|
,024
,888
38
|
,259
,117
38
|
,330*
,043
38
|
-3,58*
,027
38
|
UWMS Pearson Correlation
Sig. (2-tailed)
N
|
-,057
,733
38
|
-,387*
,016
38
|
-,197
,236
38
|
,188
,259
38
|
,024
,888
38
|
1,000
,
38
|
-,064
,703
38
|
-,203
,222
38
|
-3,63
,025
38
|
INVP Pearson Correlation
Sig. (2-tailed)
N
|
,084
,618
38
|
,105
,529
38
|
,016
,923
38
|
-,091
,586
38
|
,259
,117
38
|
-,064
,703
38
|
1,000
,
38
|
-,383
,018
38
|
,032
,851
38
|
LN Pearson Correlation
Sig. (2-tailed)
N
|
,140
,401
38
|
,219
,187
38
|
-,090
,591
38
|
-,074
,658
38
|
,330*
,043
38
|
-,203
,222
38
|
-,383
,018
38
|
1,000
,
38
|
,089
,596
38
|
moy volume Pearson Correlation
transaction jl-j125 Sig. (2-tailed)
N
|
,284
,084
38
|
,525**
,001
38
|
,132
,428
38
|
,064
,702
38
|
-,358*
,027
38
|
-.363*
,025
38
|
-,032.
,851
38
|
,089
,596
38
|
1.000
,
38
|
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
Annexe.8. Tableau de corrélations des
variables de la régression 2 du modèle.2.
Coefficients a
Model
|
Unstandardized
Coefficients
|
Standardi
zed
Coefficien
ts
|
t
|
Sig.
|
B
|
Std. Error
|
Beta
|
1 (Constant)
log RI
LAG
RUNUP
RETENTION1
LISIZE
UWMS
INVP
LN
|
33,388
,553
77,309
,694
-4,934
-4,013
-7,743
41,772
1,716
|
29,859
,586
111,319
7,979
15,062
1,858
19,212
43,365
1,608
|
,163
,125
,015
-,074
-,546
-,079
,201
,241
|
1,118
1,943
3,694
,087
-,328
-2,160
2,403
,963
1,067
|
,273
,074
,005
,931
,746
,039
,007
,343
,295
|
a. Dependent Variable: moy volume transaction j125 j500
ANOVAb
Model
|
Sum of
Squares
|
df
|
Mean
Square
|
F
|
Siq.
|
1 Regression
Residual
Total
|
464,132
1238,924
1703,056
|
8
29
37
|
58,017
42,722
|
3,358
|
,002a
|
a. Predictors: (Constant), LN, RETENTION1, LAG, RUNUP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume transaction j125 j500
Model
Summary b
Model
|
R
|
R Square
|
Adjusted
R Square
|
Std. Error
of the
Estimate
|
Durbin-W
atson
|
1
|
,722a
|
,673
|
,507
|
6,5362
|
1,271
|
a. Predictors: (Constant), LN, RETENTION1, LAG, RUNP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume transaction j125 j500
Annexe.9. Tableau de corrélations des
variables de la régression 2 du modèle.2.
Corrélation
|
log RI
|
LAG
|
RUNUP
|
RETENTION1
|
LISIZE
|
U
UUWMS
|
I
IINVP
|
LN
|
Moy de volume de
Transaction
J125-j500
|
log RI Pearson Correlation
Sig. (2-tailed)
N
|
1,000
,
38
|
,164
3,25
38
|
-,111
,509
38
|
-,291
,076
38
|
,132
,429
38
|
-,057
,733
38
|
,084
,618
38
|
,140
,401
38
|
,187
,261
38
|
LAG Pearson Correlation
Sig. (2-tailed)
N
|
,164
,325
38
|
1,000
,
38
|
-,051
,763
38
|
-,023
,891
38
|
,060
,722
38
|
-,387*
,016
38
|
,105
,529
38
|
,219
,187
38
|
,225
,174
38
|
RUNUP Pearson Correlation
Sig. (2-tailed)
N
|
-,111
,509
38
|
,051
,763
38
|
1,000
,
38
|
,210
,206
38
|
-,242
,144
38
|
-,197
,236
38
|
,016
,923
38
|
-,090
,591
38
|
,104
,535
38
|
RETENTION1 Pearson Correlation
Sig. (2-tailed)
N
|
-,291
,076
38
|
-,023
,891
38
|
,210
,206
38
|
1,000
,
38
|
-,571**
,000
38
|
,188
,259
38
|
-,091
,586
38
|
-,074
,658
38
|
,139
,404
38
|
LISIZE Pearson Correlation
Sig. (2-tailed)
N
|
,132
,429
38
|
,060
,722
38
|
,242
,144
38
|
-,571
,000
38
|
1,000
,
38
|
,024
,888
38
|
,259
,117
38
|
,330*
,043
38
|
-3,48*
,032
38
|
UWMS Pearson Correlation
Sig. (2-tailed)
N
|
-,057
,733
38
|
-,387*
,016
38
|
-,197
,236
38
|
,188
,259
38
|
,024
,888
38
|
1,000
,
38
|
-,064
,703
38
|
-,203
,222
38
|
-,228
,168
38
|
INVP Pearson Correlation
Sig. (2-tailed)
N
|
,084
,618
38
|
,105
,529
38
|
,016
,923
38
|
-,091
,586
38
|
,259
,117
38
|
-,064
,703
38
|
1,000
,
38
|
-,383*
,018
38
|
,007
,968
38
|
LN Pearson Coorelation
Sig.(2-tailed)
N
|
,140
,401
38
|
,219
,187
38
|
-,090
,591
38
|
-,074
,658
38
|
,330*
,043
38
|
-,203
,222
38
|
-,383*
,018
38
|
1,000
,
38
|
,054
,764
38
|
Moy volume Pearson Correlation transaction Sig.
(2-tailed)
j125-j500 N
|
,187
,261
38
|
,225
,174
38
|
,104
,535
38
|
,139
,404
38
|
-,348
,032
38
|
-,228
,168
38
|
,007
,968
38
|
,054
,746
38
|
1,000
,
38
|
* Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
Annexe.10. Tableau de corrélations des
variables de la régression 2 du modèle.2.
Coefficients a
Model
|
Unstandardized
Coefficients
|
Standardi
zed
Coefficien
ts
|
t
|
Sig.
|
B
|
Std. Error
|
Beta
|
1 (Constant)
Log RI
LAG
RUNP
RETENTION1
LISIZE
UWMS
INVP
LN
|
55,235
,825
231,702
2,638
-9,434
-4,909
-11,064
32,308
1,543
|
31,351
,616
116,882
8,378
15,815
1,951
20,172
45,532
1,688
|
,206
,318
,048
-,120
-,565
-,095
,132
,183
|
2,762
2,340
3,982
,315
-,597
-2,516
-3,548
,710
1,914
|
,009.
,002
,016
,755
,555
,018
,002
,484
,368
|
a. Dependent Variable: moy volume de transaction 500j
ANOVAb
Model
|
Sum of
Squares
|
df
|
Mean
Square
|
F
|
Sig.
|
1 Regression
Residual
Total
|
1014,117
1365,831
2379,948
|
8
29
37
|
126,765
47,098
|
2,692
|
,024a
|
a. Predictors: (Constant), LN, RETENTION1, LAG, RUNP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume de transaction 500j
Model Summaryb
Model
|
R
|
R Square
|
Adjusted
R Square
|
Std. Error
of the
Estimate
|
Durbin-Watson
|
1
|
,753a
|
,626
|
,527
|
,8628
|
,920
|
a. Predictors: (Constant), LN, RETENTIONI, LAG, RUNP, log RI,
INVP, UWMS, LISIZE
b. Dependent Variable: moy volume de transaction 500j
Annexe.11. Tableau de corrélations des
variables de la répression 3 du modèle.2.
Corrélations
|
moy
volume de
transaction
500j
|
log RI
|
LAG
|
RUNP
|
RETENTI
ON1
|
LISIZE
|
UWMS
|
INVP
|
LN
|
moy volume de Pearson Correlation
transaction 500) Sig. (2-tailed)
N
|
1,000
,
38
|
,256
122
38
|
.409*
011
38
|
,125
,456
38
|
,102
,543
3B
|
-,369*
023
38
|
-,321*
,049
38
|
-,016
,923
38
|
,069
,680
,38
|
log RI Pearson Correlation
Sig. (2-tailed)
N
|
256
.122
38
|
1,000
,
38
|
,164
325
38
|
-,111
,509
38
|
-,291
.076
38
|
132
.429
38
|
-,057
733
38
|
084
,618
38
|
,140
,401
,38
|
LAG Pearson Correlation
Sig. (2-tailed)
N
|
409'
,011
38
|
.164
,325
38
|
1,000
- 38
|
-,051
,763
- 38
|
-,023
891
38
|
,060
,722
38
|
-,378**
,016
38
|
,105
,529
38
|
,219
,187
,38
|
RUNP Pearson Correlation,
Sig.(2-tailed)
N
|
,125*
,456
38
|
-,111
,509
38
|
-,051
,763
38
|
1,000
,
38
|
210
,206
38
|
-,242
.144
38
|
-,197
,236
38
|
,016
,923
38
|
-,090
,511
38
|
RETENTION1 Pearson Correlation
Sig. (2-tailed)
N
|
,102
543
38
|
-,291
076
38
|
-,023
,891
38
|
210
206
38
|
1,000
,
38
|
-,571**
,000
38
|
,188
,259
38
|
-.091
586
38
|
-,074
;658
38
|
LISIZE Pearson Correlation
Sig. (2-tailed)
N
|
-,369*
,023
38
|
,132
,429
38
|
,060
,722
38
|
-,242
,144
38
|
-,571**
,000
38
|
1,000
,
38
|
,024
888
38
|
,259
,117
38
|
,330*
,043
38
|
UWMS Pearson Correlation
Sig. (2-tailed)
N
|
-,321*
,049
38
|
-,057
,733
38
|
-,387*
,016
38
|
-,197
,236
38
|
,188
,25
38
|
,024
,888
38
|
1,000
,
38
|
-,064
703
38
|
-,203
,222
38
|
INVP Pearson Correlation
Sig. (2-tailed)
N
|
-,016
,923
38
|
,084
,618
38
|
,105
,529
38
|
,016
,923
38
|
-,091
,586
38
|
,259
,117
38
|
-,064
,703
38
|
1,000
,,
38
|
-,383
,018
38
|
LN Pearson Correlation
Sig. (2-tailed)
N
|
,069
,680
38
|
,140
,401
38
|
,219
,187
38
|
-,090
,591
38
|
-,074
,658
38
|
330*
,043
38
|
-,203
,222
38
|
-,383*
,018
38
|
1,000
,
38
|
* Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
|
|