Uji Asumsi Klasik
Pengaruh Umur Siswa dan Tinggi Badan terhadap Nilai
Siswa
Variabel Terikat (Dependent Variabel):
- -
Nilai Siswa
Variabel Bebas (Independent
Variabel)
- -
Umur Siswa
- -
Jenis Kelamin Siswa
- Uji Normalitas
Titik-titik pada grafik
berada disekitar garis diagonal dan tidak menjauh dari garis. Sehingga, data
penelitian ini lulus uji normalitas.
2. Uji Multikolinearitas
Variabel jenis kelamin
siswa:
Nilai tolerance = 0,689.
Nilai tolerance > 0,1, dan
Nilai VIF = 1,451.
Nilai VIF = < 10,
Maka variabel Umur
Siswa lulus uji Multikolinearitas.
Variabel umur siswa :
Nilai tolerance = 0,689.
Nilai tolerance > 0,1, dan
Nilai VIF = 1,451.
Nilai VIF = < 10,
Maka variabel Tinggi
Badan Siswa lulus uji
Multikolinearitas.
3. Uji Heteroskedastisitas
Titik titik pada grafik
tidak membentuk suatu pola tertentu yang teratur. Dan menyebar di atas dan di
bawah angka 0 pada sumbu Y. Maka, data penelitian
ini lulus uji heteroskedastisitas.
LAMPIRAN OUTPUT SPSS
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF
OUTS R ANOVA COLLIN TOL CHANGE
/CRITERIA=PIN(.05)
POUT(.10)
/NOORIGIN
/DEPENDENT Nilai
/METHOD=ENTER Gender
Umur
/SCATTERPLOT=(*SRESID ,*ZPRED)
/RESIDUALS
NORMPROB(ZRESID).
Variables
Entered/Removeda
|
|||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Umur Siswa, Jenis Kelamin Siswab
|
.
|
Enter
|
a. Dependent Variable: Nilai Siswa
|
b. All requested variables entered.
|
Model Summaryb
|
||||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the
Estimate
|
Change Statistics
|
|
R Square Change
|
F Change
|
|||||
1
|
,499a
|
,249
|
,160
|
3,55812
|
,249
|
2,816
|
Model Summaryb
|
|||
Model
|
Change Statistics
|
||
df1
|
df2
|
Sig. F Change
|
|
1
|
2a
|
17
|
,088
|
a. Predictors: (Constant), Umur Siswa,
Jenis Kelamin Siswa
|
b. Dependent Variable: Nilai Siswa
|
ANOVAa
|
||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
71,294
|
2
|
35,647
|
2,816
|
,088b
|
Residual
|
215,224
|
17
|
12,660
|
|
|
|
Total
|
286,518
|
19
|
|
|
|
a. Dependent Variable: Nilai Siswa
|
b. Predictors: (Constant), Umur Siswa,
Jenis Kelamin Siswa
|
Coefficientsa
|
||||||
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
|
||||
1
|
(Constant)
|
70,452
|
9,733
|
|
7,239
|
,000
|
Jenis Kelamin Siswa
|
2,899
|
1,917
|
,383
|
1,512
|
,149
|
|
Umur Siswa
|
,344
|
,509
|
,171
|
,675
|
,509
|
Coefficientsa
|
|||
Model
|
Collinearity
Statistics
|
||
Tolerance
|
VIF
|
||
1
|
(Constant)
|
|
|
Jenis Kelamin Siswa
|
,689
|
1,451
|
|
Umur Siswa
|
,689
|
1,451
|
a. Dependent Variable: Nilai Siswa
|
Collinearity
Diagnosticsa
|
||||||
Model
|
Dimension
|
Eigenvalue
|
Condition Index
|
Variance Proportions
|
||
(Constant)
|
Jenis Kelamin Siswa
|
Umur Siswa
|
||||
1
|
1
|
2,636
|
1,000
|
,00
|
,04
|
,00
|
2
|
,360
|
2,704
|
,00
|
,68
|
,00
|
|
3
|
,003
|
28,830
|
1,00
|
,28
|
1,00
|
a. Dependent Variable: Nilai Siswa
|
Residuals Statisticsa
|
|||||
|
Minimum
|
Maximum
|
Mean
|
Std. Deviation
|
N
|
Predicted Value
|
76,2929
|
81,2528
|
78,7900
|
1,93709
|
20
|
Std. Predicted Value
|
-1,289
|
1,271
|
,000
|
1,000
|
20
|
Standard Error of Predicted Value
|
1,125
|
1,938
|
1,363
|
,206
|
20
|
Adjusted Predicted Value
|
76,1758
|
81,7153
|
78,7247
|
1,92506
|
20
|
Residual
|
-6,10920
|
4,02000
|
,00000
|
3,36565
|
20
|
Std. Residual
|
-1,717
|
1,130
|
,000
|
,946
|
20
|
Stud. Residual
|
-1,827
|
1,191
|
,008
|
1,018
|
20
|
Deleted Residual
|
-6,91528
|
4,53564
|
,06534
|
3,90549
|
20
|
Stud. Deleted Residual
|
-1,977
|
1,207
|
-,015
|
1,059
|
20
|
Mahal. Distance
|
,950
|
4,684
|
1,900
|
,907
|
20
|
Cook's Distance
|
,000
|
,147
|
,053
|
,051
|
20
|
Centered Leverage Value
|
,050
|
,247
|
,100
|
,048
|
20
|
a. Dependent Variable: Nilai Siswa
|
Charts