TUGAS
ANALISIS REGRESI
PERTEMUAN - 10
Nofriana D. Manafe
20160302205
UNIVERSITAS ESA UNGGUL
FAKULTAS ILMU ILMU KESEHATAN
PROGRAM STUDI ILMU GIZI
TAHUN 2017
Latihan 1
Lakukan prediksi CHOL dengan variabel independen TRIG,UM,dan UM kuadrat.
a. Hitung SS for Regression (X3 l X1, X2) ;
b. Hitung SS for Residual;
c. Hitung Mean SS for Regression (X3 l X1, X2) ;
d. Hitung Mean SS for Residual ;
e. Hitung nilai F parsial ;
f. Hitung nilai r2 ;
g. Buktikan bahwa penambahan X3 berperan memprediksi Y.
UM
|
CHOL
|
TRIG
|
UM
|
CHOL
|
TRIG
|
UM
|
CHOL
|
TRIG
|
40
|
218
|
194
|
37
|
212
|
140
|
55
|
319
|
191
|
46
|
265
|
188
|
40
|
244
|
132
|
58
|
212
|
216
|
69
|
197
|
134
|
32
|
217
|
140
|
41
|
209
|
154
|
44
|
188
|
155
|
56
|
227
|
279
|
60
|
224
|
198
|
41
|
217
|
191
|
49
|
218
|
101
|
50
|
184
|
129
|
56
|
240
|
207
|
50
|
241
|
213
|
48
|
222
|
115
|
48
|
222
|
155
|
46
|
234
|
168
|
49
|
229
|
148
|
49
|
244
|
235
|
52
|
231
|
242
|
39
|
204
|
164
|
41
|
190
|
167
|
51
|
297
|
142
|
40
|
211
|
104
|
38
|
209
|
186
|
46
|
230
|
240
|
47
|
230
|
218
|
36
|
208
|
179
|
60
|
258
|
173
|
67
|
230
|
239
|
39
|
214
|
129
|
47
|
243
|
175
|
57
|
222
|
183
|
59
|
238
|
220
|
58
|
236
|
199
|
50
|
213
|
190
|
56
|
219
|
155
|
66
|
193
|
201
|
43
|
238
|
259
|
44
|
241
|
201
|
52
|
193
|
193
|
55
|
234
|
156
|
Model 1 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
203.123
|
17.156
|
11.840
|
.000
| |
Trigliserida
|
.127
|
.093
|
.203
|
1.360
|
.181
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
1.850
Estimated model Chol = 203.123 + 0.127 Trig
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
1181.676
|
1
|
1181.676
|
1.850
|
.181a
| |
Residual
|
27464.768
|
43
|
638.716
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Trigliserida
| |||||||
b. Dependent Variable: Cholesterol
|  | ||||||
Model 2 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
204.048
|
22.093
|
9.236
|
.000
| |
Umur
|
.445
|
.444
|
.151
|
1.004
|
.321
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
1.004
Estimated model Chol = 204.048 + 0.445 UM
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
655.625
|
1
|
655.625
|
1.007
|
.321a
|
0.02
|
Residual
|
27990.819
|
43
|
650.949
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Umur
| |||||||
b. Dependent Variable: Cholesterol
| |||||||
Model 3 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
217.420
|
11.555
|
18.816
|
.000
| |
Umur Kuadrat
|
.003
|
.004
|
.118
|
.777
|
.442
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
0.562
Estimated model Chol = 217.420 + 0.003 (UM)2
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
396.227
|
1
|
396.227
|
.603
|
.442a
|
0.013
|
Residual
|
28250.217
|
43
|
656.982
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Umur Kuadrat
| |||||||
b. Dependent Variable: Cholesterol
| |||||||
Model 4 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
192.155
|
24.554
|
7.826
|
.000
| |
Trigliserida
|
.108
|
.098
|
.173
|
1.099
|
.278
| |
Umur
|
.292
|
.464
|
.099
|
.629
|
.533
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
1.214
0.396
Estimated model Chol = 192.155 + 0.108 Trig + 0.292 UM
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
1437.719
|
2
|
718.860
|
1.110
|
.339a
|
0.050
|
Residual
|
27208.725
|
42
|
647.827
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Umur, Trigliserida
| |||||||
b. Dependent Variable: Cholesterol
| |||||||
Model 5 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
200.525
|
18.433
|
10.879
|
.000
| |
Trigliserida
|
.115
|
.098
|
.185
|
1.173
|
.247
| |
Umur Kuadrat
|
.002
|
.005
|
.065
|
.413
|
.682
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
1.377
0.16
Estimated model Chol = 200.525 + 0.115 Trig + 0.002 (UM)2
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
1292.618
|
2
|
646.309
|
.992
|
.379a
|
0.045
|
Residual
|
27353.826
|
42
|
651.282
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Umur Kuadrat, Trigliserida
| |||||||
b. Dependent Variable: Cholesterol
| |||||||
Model 6 : Chol = 
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
-21.969
|
104.532
|
-.210
|
.835
| |
Trigliserida
|
.079
|
.095
|
.126
|
.825
|
.414
| |
Umur
|
9.220
|
4.269
|
3.132
|
2.160
|
.037
| |
Umur Kuadrat
|
-.088
|
.042
|
-3.035
|
-2.103
|
.042
| |
a. Dependent Variable: Cholesterol
| ||||||
Coefficient Standard Error Partial F
0.691
4.664
4.390
Estimated model Chol = -21.969 + 0.079 Trig + 9.220 UM – 0.088 (UM)2
ANOVAb
| |||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
R2
| |
1
|
Regression
|
4086.344
|
3
|
1362.115
|
2.274
|
.094a
|
0.142
|
Residual
|
24560.100
|
41
|
599.027
| ||||
Total
|
28646.444
|
44
| |||||
a. Predictors: (Constant), Umur Kuadrat, Trigliserida, Umur
| |||||||
b. Dependent Variable: Cholesterol
| |||||||
Dari ke enam model estimasi di atas kita bisa menduga model estimasi ke 6 dengan independen variable TRIG, UM dan (UM)2 adalah yang terbaik bila di lihat dari besaran r2 yaitu 0.05. Namun sebaiknya kita perhatikam uraian di bawah ini.
Kita dapat memperinci nilai-nilai Sum Square of Regression dalam tabel ANOVA sbb :
Sumber
|
df
|
SS
|
MS
|
F
|
R2
|
Regresi
X1
X2 I X1
X3 I X1,X2
|
1
1
1
|
1181.676
256.043
2648.625
|
1181.676
256.043
2648.625
|
1.972
0.395
4.42
|
0.05
|
Residual
|
41
|
24560.100
|
599.027
| ||
Total
|
44
|
28646.444
|
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