Rabu, 21 Juni 2017

Analisis Regresi Pertemuan 14

TUGAS ANALISIS REGRESI HALAMAN 222-223

Nama: Tetty H. Tinambunan
Nim: 20160302138

Latihan Halaman 222-223
ESTIMASI MODEL 1 : CHOL = 203.123 + 0.127 TRIG
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1181.676
1
1181.676
1.850
.181a
Residual
27464.768
43
638.716


Total
28646.444
44



a. Predictors: (Constant), trigliserida



b. Dependent Variable: cholesterol

Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
203.123
17.156

11.840
.000
trigliserida
.127
.093
.203
1.360
.181
a. Dependent Variable: cholesterol




ESTIMASI MODEL 2 : CHOL = 204.048 + 0.445 UMUR

ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
655.625
1
655.625
1.007
.321a
Residual
27990.819
43
650.949


Total
28646.444
44



a. Predictors: (Constant), umur




b. Dependent Variable: cholesterol




Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
204.048
22.093

9.236
.000
Umur
.445
.444
.151
1.004
.321
a. Dependent Variable: cholesterol




Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
203.123
17.156

11.840
.000
trigliserida
.127
.093
.203
1.360
.181
a. Dependent Variable: cholesterol




ESTIMASI MODEL 3 : CHOL = 217.420 +0.003 UMQS
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
396.227
1
396.227
.603
.442a
Residual
28250.217
43
656.982


Total
28646.444
44



a. Predictors: (Constant), umur kuadrat



b. Dependent Variable: cholesterol



Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
217.420
11.555

18.816
.000
umur kuadrat
.003
.004
.118
.777
.442
a. Dependent Variable: cholesterol
ESTIMASI MODEL 4 : CHOL = 192.155 + 0.292 UM + 0.108 TRIG

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), trigliserida, umur



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
Umur
.292
.464
.099
.629
.533
trigliserida
.108
.098
.173
1.099
.278
a. Dependent Variable: cholesterol




ESTIMASI MODEL 5 : CHOL = - 25.670 + 9.838 UM - 0.093 UMQS
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
3678.335
2
1839.167
3.094
.056a
Residual
24968.110
42
594.479


Total
28646.444
44



a. Predictors: (Constant), umur kuadrat, umur


b. Dependent Variable: cholesterol





Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
T
Sig.
B
Std. Error
Beta
1
(Constant)
-25.670
104.039

-.247
.806
umur
9.838
4.187
3.342
2.350
.024
umur kuadrat
-.093
.041
-3.207
-2.255
.029
a. Dependent Variable: cholesterol




ESTIMASI MODEL 6 : CHOL = - 21.969 + 9.220 UM + 0.079 TRIG - 0.088 UMQS

ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
4086.344
3
1362.115
2.274
.094a
Residual
24560.100
41
599.027


Total
28646.444
44



a. Predictors: (Constant), umur kuadrat, trigliserida, umur


b. Dependent Variable: cholesterol




Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
T
Sig.
B
Std. Error
Beta
1
(Constant)
-21.969
104.532

-.210
.835
umur
9.220
4.269
3.132
2.160
.037
trigliserida
.079
.095
.126
.825
.414
umur kuadrat
-.088
.042
-3.035
-2.103
.042
a. Dependent Variable: cholesterol




Kita lakukan uji parsial F seperti berikut (berdasarkan hasil-hasil yang sudah kita lakukan diatas)
ANOVA Tabel untuk TRIG dengan CHOL dan UM , UMSQ

Sumber
Df
SS
MS
F
r2
X1
1
1181.676
1181.676
1.97266
0.143
Regresi X2│X1
1
1.21668
1.21668
0.00203
X3│X1, X2
1
2.84224
2.84224
0.00474
Residual
41
24560.100
599.027

Total
44
28646.444



Nilai F untuk penambahan independent variabel X3 = 0.00474 <  F 4.08 ini berarti hipotesa H0 : β3 = 0 diterima atau gagal ditolak artinya penambahan third order ( X 3) tidak secara bermakna dapat memprediksi Y.

Kita bersimpulan bahwa :
  1. Penambahan “ second order” sesuai (fit)  dengan nilai r2 = 0.128
  2. Penambahan nilai rmenjadi 0.143 pada “ thind order” hanya sebesar 0.015 adalah kecil
  3. Kurva yang ada cukup diterangkan dengan “second order”


    TUGAS HALAMAN 223
    Source
    df
    SS
    MS
    F
    X
    1
    174.473,96
    174.473,96
    429,1691
    Regresi   X2│X
    1
    10.515,44
    10515,44
    25,8658
    X3│X,X2
    1
    415,19
    415,19
    1,02128
    Residual
    15
    6098,08
    406,539

    Total
    18
    190.502,93



    Model regresi :
    Model estimasi 1 : Y = - 122.345 + 6.227 X
    Model estimasi 2 : Y = 32.091 – 3.051 X + 0.1176 X2
    Model estimasi 3 : Y = 114.621 – 10.620 X + 0.3247 X2 + 0.00173 X3
    Jawaban :
    1. Nilai r2 1 : (SSY-SSE)SSY=174473.96190502.93=0.916
     2. Nilai r2 2 : (SSY-SSE)SSY=10515.44190502.93=0.05 
    3. Nilai r2 3 : (SSY-SSE)SSY=415.19190502.93=0.00218
  4. Nilai F model estimasi 1:  429.19 > F tabel 4.54, maka kesimpulan perubahan penambahan independen variabel X secara bermakna meningkatkan prediksi Y.

    5. Nilai F model estimasi 2 : 25.87  > F tabel 4.54, maka kesimpulan perubahan penambahan independen variabel X2  secara bermakna meningkatkan prediksi Y.

    6. Nilai F model estimasi 3 : 1.02  > F tabel 4.54, maka kesimpulan perubahan penambahan independen variabel X  tidak secara bermakna meningkatkan prediksi Y

    7. Model yang terbaik Y = -122.345 + 6.227X