TUGAS HALAMAN
221
ESTIMASI MODEL 1 : TRIG =167.677 - 0.792 IMT
ANOVAb
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Model
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Sum of Squares
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df
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Mean Square
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F
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Sig.
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1
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Regression
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601.667
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1
|
601.667
|
.371
|
.547a
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Residual
|
48697.302
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30
|
1623.243
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|
|
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Total
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49298.969
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31
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a.
Predictors: (Constant), indeksmassatubuh
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b.
Dependent Variable: trigliserida
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Coefficientsa
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Model
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Unstandardized Coefficients
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Standardized Coefficients
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t
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Sig.
|
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B
|
Std. Error
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Beta
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||||
1
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(Constant)
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167.677
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46.066
|
|
3.640
|
.001
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indeksmassatubuh
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-.792
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1.300
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-.110
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-.609
|
.547
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a.
Dependent Variable: trigliserida
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ESTIMASI MODEL 2 : TRIG = 149.943 - 0.177 UMUR
ANOVAb
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Model
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Sum of Squares
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Df
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Mean Square
|
F
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Sig.
|
|
1
|
Regression
|
212.189
|
1
|
212.189
|
.130
|
.721a
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Residual
|
49086.780
|
30
|
1636.226
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|
|
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Total
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49298.969
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31
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a.
Predictors: (Constant), umur
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b.
Dependent Variable: trigliserida
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Coefficientsa
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||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
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||||
1
|
(Constant)
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149.943
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28.605
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|
5.242
|
.000
|
umur
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-.177
|
.492
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-.066
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-.360
|
.721
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a.
Dependent Variable: trigliserida
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ESTIMASI MODEL 3 : TRIG = 142.230 + 0.000 UMUR KUADRAT
ANOVAb
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||||||
Model
|
Sum of Squares
|
df
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Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
85.385
|
1
|
85.385
|
.052
|
.821a
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Residual
|
49213.584
|
30
|
1640.453
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|
|
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Total
|
49298.969
|
31
|
|
|
|
|
a.
Predictors: (Constant), umurkuadrat
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|
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|||
b.
Dependent Variable: trigliserida
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|
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|
Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
|
||||
1
|
(Constant)
|
142.230
|
12.226
|
|
11.634
|
.000
|
umurkuadrat
|
.000
|
.003
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-.042
|
-.228
|
.821
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a.
Dependent Variable: trigliserida
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ESTIMASI MODEL 4 :167.688 - 0.784 IMT - 0.005 UMUR
ANOVAb
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||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
601.777
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2
|
300.889
|
.179
|
.837a
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Residual
|
48697.191
|
29
|
1679.213
|
|
|
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Total
|
49298.969
|
31
|
|
|
|
|
a.
Predictors: (Constant), umur, indeksmassatubuh
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|
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||||
b.
Dependent Variable: trigliserida
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|
|
|
Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
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||||
1
|
(Constant)
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167.688
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46.872
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|
3.578
|
.001
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indeksmassatubuh
|
-.784
|
1.628
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-.109
|
-.482
|
.634
|
|
Umur
|
-.005
|
.613
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-.002
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-.008
|
.994
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a.
Dependent Variable: trigliserida
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ESTIMASI MODEL 5 :168.623 - 0.841 IMT + 0.000 UMUR KUADRAT
ANOVAb
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||||||
Model
|
Sum of Squares
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df
|
Mean Square
|
F
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Sig.
|
|
1
|
Regression
|
609.613
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2
|
304.806
|
.182
|
.835a
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Residual
|
48689.356
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29
|
1678.943
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|
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Total
|
49298.969
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31
|
|
|
|
|
a.
Predictors: (Constant), umurkuadrat, indeksmassatubuh
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|
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||||
b.
Dependent Variable: trigliserida
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|
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Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
|
||||
1
|
(Constant)
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168.623
|
48.827
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|
3.453
|
.002
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indeksmassatubuh
|
-.841
|
1.505
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-.117
|
-.559
|
.581
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|
umurkuadrat
|
.000
|
.003
|
.014
|
.069
|
.946
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a.
Dependent Variable: trigliserida
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ESTIMASI MODEL 6 :214.510 - 0.107 IMT - 1.886 UMUR + 0.010 UMUR KUADRAT
ANOVAb
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||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
1002.559
|
3
|
334.186
|
.194
|
.900a
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Residual
|
48296.409
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28
|
1724.872
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Total
|
49298.969
|
31
|
|
|
|
|
a.
Predictors: (Constant), umurkuadrat, indeksmassatubuh, umur
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|||||
b.
Dependent Variable: trigliserida
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|
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|
Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
B
|
Std. Error
|
Beta
|
||||
1
|
(Constant)
|
214.510
|
108.129
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|
1.984
|
.057
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indeksmassatubuh
|
-.107
|
2.166
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-.015
|
-.050
|
.961
|
|
Umur
|
-1.886
|
3.951
|
-.699
|
-.477
|
.637
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umurkuadrat
|
.010
|
.022
|
.653
|
.482
|
.634
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a.
Dependent Variable: trigliserida
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Kita
lakukanujiparsial F sepertiberikut (berdasarkanhasil-hasil yang
sudahkitalakukandiatas)
ANOVA Tabeluntuk
TRIG denganIMTdanUM , UMSQ
Sumber
|
Df
|
SS
|
MS
|
F
|
r2
|
X1
|
1
|
601.667
|
601.667
|
0.34881
|
0.900
|
Regresi X2│X1
|
1
|
1.00018
|
1.00018
|
0.00058
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X3│X1, X2
|
1
|
1.66600
|
1.66600
|
0.00966
|
|
Residual
|
28
|
48296.409
|
1724.872
|
||
Total
|
31
|
49298.969
|
Nilai F
untukpenambahan independent variabel X3 = 0.00966 < F 4.02
iniberartihipotesa H0 : β3 = 0 diterimaataugagalditolakartinyapenambahan
third order ( X 3) tidaksecarabermaknadapatmemprediksi Y.
Kita
bersimpulanbahwa :
a.
Penambahan “ second order” sesuai
(fit) dengannilai r2 = 0.021
b.
Penambahannilai r2 menjadi0.900 pada “ thind
order” hanyasebesar 0879 adalahkecil
c.
Kurva yang adacukupditerangkandengan “second order”
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