Analisis Regresi pertemuan 13
TUGAS ANALISIS REGRESI HALAMAN 221
Lakukan prediksi TRI dengan variabel independen IMT, Umur dan Umur kuadrat
Bekerja bersama di Laboratorium
- Lakukan analisa regresi masing-masing independen variabel
- Hitung SS for Regression (X3|X1,X2)
- Hitung SS for Residual
- Hitung mean SS for Regression (X3|X1,X2)
- Hitung mean SS for Residual
- Hitung nilai F parsial
- Hitung nilai r2
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
601.667
|
1
|
601.667
|
.371
|
.547a
|
Residual
|
48697.302
|
30
|
1623.243
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), indeks massa tubuh
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
167.677
|
46.066
|
3.640
|
.001
| |
indeks massa tubuh
|
-.792
|
1.300
|
-.110
|
-.609
|
.547
| |
a. Dependent Variable: trigliserida
| ||||||
ESTIMASI MODEL 2 : TRIG = 149.943 - 0.177 UMUR
ANOVAb
| ||||||
Model
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
212.189
|
1
|
212.189
|
.130
|
.721a
|
Residual
|
49086.780
|
30
|
1636.226
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), umur
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
149.943
|
28.605
|
5.242
|
.000
| |
umur
|
-.177
|
.492
|
-.066
|
-.360
|
.721
| |
a. Dependent Variable: trigliserida
| ||||||
ESTIMASI MODEL 3 : TRIG = 142.230 + 0.000 UMUR KUADRAT
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
85.385
|
1
|
85.385
|
.052
|
.821a
|
Residual
|
49213.584
|
30
|
1640.453
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), umur kuadrat
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
142.230
|
12.226
|
11.634
|
.000
| |
umur kuadrat
|
.000
|
.003
|
-.042
|
-.228
|
.821
| |
a. Dependent Variable: trigliserida
| ||||||
ESTIMASI MODEL 4 : 167.688 - 0.784 IMT - 0.005 UMUR
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
601.777
|
2
|
300.889
|
.179
|
.837a
|
Residual
|
48697.191
|
29
|
1679.213
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), umur, indeks massa tubuh
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
167.688
|
46.872
|
3.578
|
.001
| |
indeks massa tubuh
|
-.784
|
1.628
|
-.109
|
-.482
|
.634
| |
Umur
|
-.005
|
.613
|
-.002
|
-.008
|
.994
| |
a. Dependent Variable: trigliserida
| ||||||
ESTIMASI MODEL 5 : 168.623 - 0.841 IMT + 0.000 UMUR KUADRAT
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
609.613
|
2
|
304.806
|
.182
|
.835a
|
Residual
|
48689.356
|
29
|
1678.943
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), umur kuadrat, indeks massa tubuh
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
168.623
|
48.827
|
3.453
|
.002
| |
indeks massa tubuh
|
-.841
|
1.505
|
-.117
|
-.559
|
.581
| |
umur kuadrat
|
.000
|
.003
|
.014
|
.069
|
.946
| |
a. Dependent Variable: trigliserida
| ||||||
ESTIMASI MODEL 6 : 214.510 - 0.107 IMT - 1.886 UMUR + 0.010 UMUR KUADRAT
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
1002.559
|
3
|
334.186
|
.194
|
.900a
|
Residual
|
48296.409
|
28
|
1724.872
| |||
Total
|
49298.969
|
31
| ||||
a. Predictors: (Constant), umur kuadrat, indeks massa tubuh, umur
| ||||||
b. Dependent Variable: trigliserida
| ||||||
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
214.510
|
108.129
|
1.984
|
.057
| |
indeks massa tubuh
|
-.107
|
2.166
|
-.015
|
-.050
|
.961
| |
Umur
|
-1.886
|
3.951
|
-.699
|
-.477
|
.637
| |
umur kuadrat
|
.010
|
.022
|
.653
|
.482
|
.634
| |
a. Dependent Variable: trigliserida
| ||||||
Kita lakukan uji parsial F seperti berikut (berdasarkan hasil-hasil yang sudah kita lakukan diatas)
ANOVA Tabel untuk TRIG dengan IMT dan UM , UMSQ
Sumber
|
Df
|
SS
|
MS
|
F
|
r2
|
X1
|
1
|
601.667
|
601.667
|
0.34881
|
0.900
|
Regresi X2│X1
|
1
|
1.00018
|
1.00018
|
0.00058
| |
X3│X1, X2
|
1
|
1.66600
|
1.66600
|
0.00966
| |
Residual
|
28
|
48296.409
|
1724.872
| ||
Total
|
31
|
49298.969
|
Nilai F untuk penambahan independent variabel X3 = 0.00966 < F 4.02 ini berarti hipotesa H0 : β3 = 0 diterima atau gagal ditolak artinya penambahan third order ( X 3) tidak secara bermakna dapat memprediksi Y.
Kita bersimpulan bahwa :
a. Penambahan “ second order” sesuai (fit) dengan nilai r2 = 0.021
b. Penambahan nilai r2 menjadi 0.900 pada “ thind order” hanya sebesar 0879 adalah kecil
c. Kurva yang ada cukup diterangkan dengan “second order”
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