NAMA : DANIEL SASMITRO WIBOWO
NIM : 20160302246
HAL 123
LATIHAN
1. Lakukan prediksi CHOL dengan variabel independen TRIG dan UM :
a. Hitung Sum of Square for Regression (X)
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
d. Hitung Means Sum of Square for Residual
e. Hitung nilai F
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
|
f. Hitung nilai r2
g. Tulis Model Regresi
UM = Umur
CHOL = Cholesterol
TRIG = Trigliserida
Jawaban :
Variables Entered/Removed
| |||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Umur, Trigliseridaa
|
.
|
Enter
|
a. All requested variables entered.
b. Dependent Variable: Cholesterol
|
Model Summary
| ||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.224a
|
.050
|
.005
|
25.452
|
a. Predictors: (Constant), Umur, Trigliserida
|
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
1437.719
|
2
|
718.860
|
1.110
|
.339a
|
Residual
|
27208.725
|
42
|
647.827
| |||
Total
|
28646.444
|
44
| ||||
a. Predictors: (Constant), Umur, Trigliserida
| ||||||
b. Dependent Variable: Cholesterol
|
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
|
a. Hitung Sum of Square for Regression (X)
SSY – SSE = 28646.444 – 27208.725 = 1437.719
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
SSRegr / df = 1437.719 / 2 = 718.860
d. Hitung Means Sum of Square for Residual
SSResd / df = 27208.725 / 42 = 647.827
e. Hitung nilai F
F = MS – Regr / MS – Resd = 718.860 / 647.827 = 1.110
f. Hitung nilai r2 = 0.050
Model Regresi
CHOL = 192.155+ 0.108 TRIG + 0.292 UM
Perhatikan nilai t untuk masing-masing parameter dan signifikansinya.
Pada individu yang berumur 55 tahun dengan TRIG = 156, maka Cholesterol nya diprediksi sebesar :
= 192.155+ (0.108*156) + (0.292*55)
= 192.155+ 16.848 + 16.06
= 225.063 dibulatkan menjadi 225
Pada individu yang berumur 67 tahun dengan TRIG = 239, maka Cholesterol nya diprediksi sebesar :
= 192.155+ (0.108*239) + (0.292*67)
= 192.155+ 25.812 + 19.564
= 237.531 dibulatkan menjadi 238
2. Lakukan prediksi Berat Badan (BB) dengan variabel independen Tinggi Badan (TB), Berat Badan Tanpa Lemak (BTL) dan Asupan Kalori (AK) :
a. Hitung Sum of Square for Regression (X)
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
d. Hitung Means Sum of Square for Residual
e. Hitung nilai F
f. Hitung nilai r2
g. Tulis Model Regresi
BB
|
TB
|
BTL
|
AK
|
79.2
|
149
|
54.1
|
2670
|
64.0
|
152
|
44.3
|
820
|
67.0
|
155.7
|
47.8
|
1210
|
78.4
|
159
|
53.9
|
2678
|
66.0
|
163.3
|
47.5
|
1205
|
63.0
|
166
|
43
|
815
|
65.9
|
169
|
47.1
|
1200
|
63.1
|
172
|
44.0
|
1180
|
73.2
|
174.5
|
44.1
|
1850
|
66.5
|
176.1
|
48.3
|
1260
|
61.9
|
176.5
|
43.5
|
1170
|
72.5
|
179
|
43.3
|
1852
|
101.1
|
182
|
66.4
|
1790
|
66.2
|
170.4
|
47.5
|
1250
|
99.9
|
184.9
|
66
|
1889
|
63.0
|
169
|
44
|
915
|
BB = Berat Badan
TB = Tinggi Badan
BTL = Berat Tanpa Lemak
AK = Asupan Kalori
Jawaban :
Variables Entered/Removed
| |||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Asupan Kalori, Tinggi Badan, Berat Tanpa Lemaka
|
.
|
Enter
|
a. All requested variables entered.
b. Dependent Variable: Berat Badan
|
Model Summary
| ||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.969a
|
.939
|
.923
|
3.4224
|
a. Predictors: (Constant), Asupan Kalori, Tinggi Badan, Berat Tanpa Lemak
|
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
2148.400
|
3
|
716.133
|
61.141
|
.000a
|
Residual
|
140.554
|
12
|
11.713
| |||
Total
|
2288.954
|
15
| ||||
a. Predictors: (Constant), Asupan Kalori, Tinggi Badan, Berat Tanpa Lemak
| ||||||
b. Dependent Variable: Berat Badan
|
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
-33.412
|
14.489
|
-2.306
|
.040
| |
Tinggi Badan
|
.210
|
.090
|
.180
|
2.339
|
.037
| |
Berat Tanpa Lemak
|
1.291
|
.150
|
.785
|
8.631
|
.000
| |
Asupan Kalori
|
.004
|
.002
|
.209
|
2.375
|
.035
| |
a. Dependent Variable: Berat Badan
|
a. Hitung Sum of Square for Regression (X)
SSY – SSE = 2288.954 – 140.554 = 2148.400
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
SSRegr / df = 2148.400 / 3 = 716.133
d. Hitung Means Sum of Square for Residual
SSResd / df = 140.554 / 12 = 11.713
e. Hitung nilai F
F = MS – Regr / MS – Resd = 716.133 / 11.713 = 61.140
f. Hitung nilai r2 = 0. 939
Model Regresi
BB = -33.412 + 0.210 TB + 1.291 BTL + 0.004 AK
Perhatikan nilai t untuk masing-masing parameter dan signifikansinya.
Pada individu memiliki Tinggi Badan = 184.9 dengan Berat Badan Tanpa Lemak = 66 dan Asupan Kalori = 1889, maka Berat badan nya diprediksi sebesar :
= -33.412 + (0.210*184.9) + (1.291*66) + (0.004*1889)
= -33.412 + 38.829 + 85.206 + 7.556
= 98.179 dibulatkan menjadi 98
Pada individu memiliki Tinggi Badan = 152 dengan Berat Badan Tanpa Lemak = 44.3 dan Asupan Kalori = 820, maka Berat badan nya diprediksi sebesar :
= -33.412 + (0.210*152) + (1.291*44.3) + (0.004*820)
= -33.412 + 31.92 + 57.1913 + 3.28
= 58.9793 dibulatkan menjadi 59
NAMA : DININGRUM FERAYUDHA
NIM : 20160302230
HAL : 118
LATIHAN
Lakukan prediksi TDS dengan variabel independen IMT dan UM :
a. Hitung Sum of Square for Regression (X)
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
d. Hitung Means Sum of Square for Residual
e. Hitung nilai F
f. Hitung nilai r2
TDS
|
IMT
|
UM
|
TDS
|
IMT
|
UM
|
TDS
|
IMT
|
UM
|
135
|
28
|
45
|
122
|
32
|
41
|
130
|
31
|
49
|
148
|
37
|
52
|
146
|
29
|
54
|
129
|
28
|
47
|
162
|
37
|
60
|
160
|
36
|
48
|
144
|
23
|
44
|
180
|
46
|
64
|
166
|
39
|
59
|
138
|
40
|
51
|
152
|
41
|
64
|
138
|
36
|
56
|
140
|
35
|
54
|
134
|
30
|
50
|
145
|
34
|
49
|
142
|
30
|
46
|
135
|
32
|
57
|
142
|
34
|
56
|
144
|
37
|
58
|
137
|
33
|
53
|
132
|
32
|
50
|
149
|
33
|
54
|
132
|
30
|
48
|
120
|
28
|
43
|
126
|
29
|
43
|
161
|
38
|
63
|
170
|
41
|
63
|
152
|
39
|
62
|
TDS = Tekanan Darah Sistolik
IMT = Indeks Massa Tubuh
UM = Umur
Jawaban :
Variables Entered/Removed
| |||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Umur, Indeks Massa Tubuha
|
.
|
Enter
|
a. All requested variables entered.
b. Dependent Variable: Tekanan Darah Sistolik
|
Model Summary
| ||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.785a
|
.616
|
.588
|
9.233
|
a. Predictors: (Constant), Umur, Indeks Massa Tubuh
|
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
3694.398
|
2
|
1847.199
|
21.667
|
.000a
|
Residual
|
2301.902
|
27
|
85.256
| |||
Total
|
5996.300
|
29
| ||||
a. Predictors: (Constant), Umur, Indeks Massa Tubuh
| ||||||
b. Dependent Variable: Tekanan darah sistolik
|
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
56.585
|
13.481
|
4.197
|
.000
| |
Indeks Massa Tubuh
|
.994
|
.569
|
.347
|
1.749
|
.092
| |
Umur
|
1.011
|
.418
|
.479
|
2.417
|
.023
| |
a. Dependent Variable: Tekanan darah sistolik
|
a. Hitung Sum of Square for Regression (X)
SSY – SSE = 5996.300 – 2301.902 = 3694.398
b. Hitung Sum of Square for Residual
c. Hitung Means Sum of Square for Regression (X)
SSRegr / df = 3694.398 / 2 = 1847.199
d. Hitung Means Sum of Square for Residual
SSResd / df = 2301.902 / 27 = 85.256
e. Hitung nilai F
F = MS – Regr / MS – Resd = 1847.199 / 85.256 = 21.666
f. Hitung nilai r2 = 0.616
Model Regresi
TDS = 56.585 + 0.994 IMT + 1.011 UM
Perhatikan nilai t untuk masing-masing parameter dan signifikansinya.
Pada individu yang berumur 50 tahun dengan IMT = 28, maka Tekanan Darah Sistolik nya diprediksi sebesar :
= 56.585 + (0.994*28) + (1.011*50)
= 56.585 + 27.832 +50.55
= 134.382 dibulatkan menjadi 134
Pada individu yang berumur 60 tahun dengan IMT = 30, maka Tekanan Darah Sistolik nya diprediksi sebesar :
= 56.585 + (0.994*30) + (1.011*60)
= 56.585 + 29.82 + 60.66
= 147.065 dibulatkan menjadi 147
Pada individu yang berumur 65 tahun dengan IMT = 25, maka Tekanan Darah Sistolik nya diprediksi sebesar :
= 56.585 + (0.994*25) + (1.011*65)
= 56.585 + 24.85 + 65.715
= 147.150 dibulatkan menjadi 147
Tidak ada komentar:
Posting Komentar