Nama : Umi Kholifah
Nim : 201532242
- Prediksi Kolesterol dengan variabel independent Trigliserid dan Umur (Hal 123)
Variables Entered/Removedb
| ||||
Model
|
Variables Entered
|
Variables Removed
|
Method
| |
dimension0
|
1
|
umur, kadar trigia
|
.
|
Enter
|
a. All requested variables entered.
| ||||
b. Dependent Variable: kadar ko
|
Model Summary
| |||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
| |
dimension0
|
1
|
,969a
|
,939
|
,923
|
3,4224
|
a. Predictors: (Constant), Asupan Kalori, Tinggi Badan, Berat Badan Tanpa Lemak
|
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, kadar trigi
| ||||||
b. Dependent Variable: kadar ko
|
Coefficientsa
| ||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
| ||
B
|
Std. Error
|
Beta
| ||||
1
|
(Constant)
|
192,155
|
24,554
|
7,826
|
,000
| |
kadar trigi
|
,108
|
,098
|
,173
|
1,099
|
,278
| |
Umur
|
,292
|
,464
|
,099
|
,629
|
,533
| |
a. Dependent Variable: kadar ko
|
- Sum Of Square for Regression
= 28646,444 – 27208,725
= 1437,719
- Sum of Square for Residual
= 27208,725
- Means Sum of Square for Regression
SSRegr / df = 1437,719 / 2
= 718,860
- Means Sum of Square for Residual
SSResd / df = 27208,725 / 42
= 647,827
- Nilai F
F = MS-Regr / MS-Resd = 718,860/647,827 = 1,110
- Nilai r2
- Model Regresi
Kadar Cholesterol = 192,155 + 0,108 kadar trigliserida + 0,292 umur
- Prediksi Berat Badan dengan variabelbindependent Tinggi Badan, Berat Badan tanpa Lemak dan Asupan Kalori (Hal 124)
Variables Entered/Removedb
| ||||
Model
|
Variables Entered
|
Variables Removed
|
Method
| |
dimension0
|
1
|
Asupan Kalori, Tinggi Badan, Berat Badan 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
| |
dimension0
|
1
|
,969a
|
,939
|
,923
|
3,4224
|
a. Predictors: (Constant), Asupan Kalori, Tinggi Badan, Berat Badan 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 Badan 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 Badan Tanpa Lemak
|
1,291
|
,150
|
,785
|
8,631
|
,000
| |
Asupan Kalori
|
,004
|
,002
|
,209
|
2,375
|
,035
| |
a. Dependent Variable: Berat Badan
|
- Sum o Square for Regression
= 2288,954 - 140,554 = 2148,400
- Sum of Square for Residual
= 140,554
- Means Sum o Square for Regression
SSRegr / df = 2148,400/3 = 716,133
- Means Sum of Square for Residual
SSResd / df = 140,554 / 12 = 11,713
- Nilai F
F = MS-Regr / MS-Resd =
- Nilai r2
- Model Regression
Berat Badan = -33,412 +0,210 Tinggi Badan + 1,291 Berat badan tanpa lemak + 0,004 asupan kalori
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