NAMA : DININGRU
FERAYUDHA
NIM :
20160302230
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
Komentar
Posting Komentar