TUGAS ANALISIS REGRESI
1. Lakukan prediksi CHOL dengan variable independen TRIG dan UM:
a. Hitung SS for Regression
b. Hitung SS for Residual
c. Hitung MSS for Regression
d. Hitung MSS for Residual
e. Hitung Nilai F
f. Hitung Nilai r²
g. Tulis model regresi
UM
|
CHOL
|
TRIG
|
UM
|
CHOL
|
TRIG
|
UM
|
CHOL
|
TRIG
|
40.0
|
218.0
|
194.0
|
37.0
|
212.0
|
140.0
|
55.0
|
319.0
|
191.0
|
46.0
|
265.0
|
188.0
|
49.0
|
244.0
|
132.0
|
58.0
|
212.0
|
216.0
|
69.0
|
197.0
|
134.0
|
32.0
|
217.0
|
140.0
|
41.0
|
209.0
|
154.0
|
44.0
|
188.0
|
155.0
|
56.0
|
227.0
|
279.0
|
60.0
|
224.0
|
198.0
|
41.0
|
217.0
|
191.0
|
49.0
|
218.0
|
101.0
|
50.0
|
184.0
|
129.0
|
56.0
|
240.0
|
207.0
|
50.0
|
241.0
|
213.0
|
48.0
|
222.0
|
115.0
|
48.0
|
222.0
|
155.0
|
46.0
|
234.0
|
168.0
|
49.0
|
229.0
|
148.0
|
49.0
|
244.0
|
235.0
|
52.0
|
231.0
|
242.0
|
39.0
|
204.0
|
164.0
|
41.0
|
190.0
|
167.0
|
51.0
|
297.0
|
142.0
|
40.0
|
211.0
|
104.0
|
38.0
|
209.0
|
186.0
|
46.0
|
230.0
|
240.0
|
47.0
|
230.0
|
218.0
|
36.0
|
208.0
|
179.0
|
60.0
|
258.0
|
173.0
|
67.0
|
230.0
|
239.0
|
39.0
|
214.0
|
129.0
|
47.0
|
243.0
|
175.0
|
57.0
|
222.0
|
183.0
|
59.0
|
238.0
|
220.0
|
58.0
|
236.0
|
199.0
|
50.0
|
213.0
|
190.0
|
56.0
|
219.0
|
155.0
|
66.0
|
193.0
|
201.0
|
43.0
|
238.0
|
259.0
|
44.0
|
241.0
|
201.0
|
52.0
|
193.0
|
193.0
|
55.0
|
234.0
|
156.0
|
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
1584.648
|
2
|
792.324
|
1.230
|
.303a
|
Residual
|
27061.796
|
42
|
644.328
| |||
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)
|
188.831
|
24.971
|
7.562
|
.000
| |
TRIGLISERIDA
|
.105
|
.097
|
.169
|
1.082
|
.285
| |
UMUR
|
.368
|
.465
|
.123
|
.791
|
.433
| |
a. Dependent Variable: CHOLESTEROL
|
JAWAB:
a. SS for Regression
SSY – SSE = 28646,444 – 27061.796 = 1584.648
b. SS for Residual = 27061.796
c. MSS for Regression
SSReg : df = 1584.648 : 2 = 792.324
d. MSS for Residual
SSE : df = 27061.796 : 42 = 644.328
e. Nilai F
MSSReg : MSSRes ; 792.324 : 644.328 = 1.230
f. Nilai r²
(SSY – SSE) : SSY = (28646.444 – 27061.796) : 28646.444 = 0.055
g. Model regresi
CHOL = 188.831 + 0.10 TRIG + 0.368 UM
2. Lakukan prediksi BB dengan variable independen TB, BTL, AK
h. Hitung SS for Regression
i. Hitung SS for Residual
j. Hitung MSS for Regression
k. Hitung MSS for Residual
l. Hitung Nilai F
m. Hitung Nilai r²
n. Tulis model regresi
BB
|
TB
|
BTL
|
AK
|
BB
|
TB
|
BTL
|
AK
|
79.2
|
149.0
|
54.1
|
2670.0
|
73.2
|
174.5
|
44.1
|
1850.0
|
64.0
|
152.0
|
44.3
|
820.0
|
66.5
|
176.1
|
48.3
|
1260.0
|
67.0
|
155.7
|
57.8
|
1210.0
|
61.9
|
176.5
|
43.5
|
1170.0
|
78.4
|
159.0
|
53.9
|
2678.0
|
72.5
|
179.0
|
43.3
|
1853.0
|
66.0
|
163.3
|
47.5
|
1205.0
|
101.1
|
182.0
|
66.4
|
1790.0
|
63.0
|
166.0
|
43.0
|
815.0
|
66.2
|
170.4
|
47.5
|
1250.0
|
65.9
|
169.0
|
47.1
|
1200.0
|
99.9
|
184.9
|
66.0
|
1889.0
|
63.1
|
172.0
|
44.0
|
1180.0
|
63.0
|
169.0
|
44.0
|
915.0
|
ANOVAb
| ||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
| |
1
|
Regression
|
2059.411
|
3
|
686.470
|
35.887
|
.000a
|
Residual
|
229.543
|
12
|
19.129
| |||
Total
|
2288.954
|
15
| ||||
a. Predictors: (Constant), ASUPAN KALORI, TINGGI BADAN, BERAT BADAN TANPA LEMAK
| ||||||
b. Dependent Variable: BERAT BADAN
|
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
-49.208
|
18.723
|
-2.628
|
.022
| |
TINGGI BADAN
|
.343
|
.110
|
.293
|
3.128
|
.009
| |
BERAT BADAN TANPA LEMAK
|
1.076
|
.168
|
.681
|
6.401
|
.000
| |
ASUPAN KALORI
|
.007
|
.002
|
.313
|
2.976
|
.012
| |
a. Dependent Variable: BERAT BADAN
|
JAWAB:
a. SS for Regression
SSY – SSE = 2288.954 – 229.543 = 2059.411
b. SS for Residual = 229.543
c. MSS for Regression
SSReg : df = 2059.411 : 3 = 686.470
d. MSS for Residual
SSE : df = 229.543 : 12 = 19.129
e. Nilai F
MSSReg : MSSRes = 686.470 : 19.129 = 35.887
f. Nilai r²
(SSY – SSE) : SSY = (2288.954 – 229.543) : 2288.954 = 0.900
g. Model regresi
BB = -49.208 + 0.343 TB + 1.076 BTL + 0.007 AK
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