Nama: fentra angaeni
Nim: 20160302163
Tugas: halaman 153
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
|
|
40
|
218
|
194
|
|
46
|
265
|
188
|
|
69
|
197
|
134
|
|
44
|
188
|
155
|
|
41
|
217
|
191
|
|
56
|
240
|
207
|
|
48
|
222
|
155
|
|
49
|
244
|
235
|
|
41
|
190
|
167
|
|
38
|
209
|
186
|
|
36
|
208
|
179
|
|
39
|
214
|
129
|
|
59
|
238
|
220
|
|
56
|
219
|
155
|
|
44
|
241
|
201
|
|
37
|
212
|
140
|
|
40
|
244
|
132
|
|
32
|
217
|
140
|
|
56
|
227
|
279
|
|
49
|
218
|
101
|
|
50
|
241
|
213
|
|
46
|
234
|
168
|
|
52
|
231
|
242
|
|
51
|
297
|
142
|
|
46
|
230
|
240
|
|
60
|
258
|
173
|
|
47
|
243
|
175
|
|
58
|
236
|
199
|
|
66
|
193
|
201
|
|
52
|
193
|
193
|
|
55
|
319
|
191
|
|
58
|
212
|
216
|
|
41
|
209
|
154
|
|
60
|
224
|
198
|
|
50
|
184
|
129
|
|
48
|
222
|
115
|
|
49
|
229
|
148
|
|
39
|
204
|
164
|
|
40
|
211
|
104
|
|
47
|
230
|
218
|
|
67
|
230
|
239
|
|
57
|
222
|
183
|
|
50
|
213
|
190
|
|
43
|
238
|
259
|
|
55
|
234
|
156
|
Model
1 : Chol = β0 + β1 Trig + E
|
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
β0 = 203.123
β1 =
0.127 S
β1 = 0,93 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 = β0 + β1
UM + E
|
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
β0 = 204.408
β1 =
0.445 S
β1 = 0.444 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 = β0 + β1 (UM)2 +
E
|
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
β0 = 217.420
β1 =
0.003
S
β1 = 0.444 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 = β0 + β1
Trig + β1 UM + E
|
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
β0 = 192.155
β1 =
0.108
S β1 = 0.444 1.214
β1
= 0.292 S β2
= 0.464 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
|
|||||||
|
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
|
|||||||
|
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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