Febi Khairunnisa (201532081)
Analisa Regresi Sesi 11
Tugas Hal 70
Latihan
1
Lakukan uji kualitas garis lurus dan hipotesa slope
dan intersep.
Kasus
|
IMT
|
GPP
|
Kasus
|
IMT
|
GPP
|
Kasus
|
IMT
|
GPP
|
1
|
18.6
|
150
|
10
|
18.2
|
120
|
19
|
27.0
|
140
|
2
|
28.1
|
150
|
11
|
17.9
|
130
|
20
|
18.9
|
100
|
3
|
25.1
|
120
|
12
|
21.8
|
140
|
21
|
16.7
|
100
|
4
|
21.6
|
150
|
13
|
16.1
|
100
|
22
|
18.5
|
170
|
5
|
28.4
|
190
|
14
|
21.5
|
150
|
23
|
19.4
|
150
|
6
|
20.8
|
110
|
15
|
24.5
|
130
|
24
|
24.0
|
160
|
7
|
23.2
|
150
|
16
|
23.7
|
180
|
25
|
26.8
|
200
|
8
|
15.9
|
130
|
17
|
21.9
|
140
|
26
|
28.7
|
190
|
9
|
16.4
|
130
|
18
|
18.6
|
135
|
27
|
21.0
|
120
|
Latihan
2
Subjek
|
Berat Badan (Kg)
|
Glukosa (mg/100ml)
|
Subjek
|
Berat Badan (Kg)
|
Glukosa (mg/100ml)
|
1
|
64.0
|
108
|
9
|
82.1
|
101
|
2
|
75.3
|
109
|
10
|
78.9
|
85
|
3
|
73.0
|
104
|
11
|
76.7
|
99
|
4
|
82.1
|
102
|
12
|
82.1
|
100
|
5
|
76.2
|
105
|
13
|
83.9
|
108
|
6
|
95.7
|
121
|
14
|
73.0
|
104
|
7
|
59.4
|
79
|
15
|
64.4
|
102
|
8
|
93.4
|
107
|
16
|
77.6
|
87
|
Latihan
1
Hasil
Output SPSS
Regression
Notes
|
||
Output Created
|
30-Mar-2016 09:46:35
|
|
Comments
|
||
Input
|
Active Dataset
|
DataSet2
|
Filter
|
<none>
|
|
Weight
|
<none>
|
|
Split File
|
<none>
|
|
N of Rows in Working Data File
|
27
|
|
Missing Value Handling
|
Definition of Missing
|
User-defined missing values are treated as missing.
|
Cases Used
|
Statistics are based on cases with no missing values
for any variable used.
|
|
Syntax
|
REGRESSION
/MISSING
LISTWISE
/STATISTICS
COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT GPP
/METHOD=ENTER
IMT.
|
|
Resources
|
Processor Time
|
0:00:00.063
|
Elapsed Time
|
0:00:01.170
|
|
Memory Required
|
1356 bytes
|
|
Additional
Memory Required for Residual Plots
|
0 bytes
|
|
[DataSet2]
Variables Entered/Removedb
|
|||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Indeks Masa tubuha
|
.
|
Enter
|
a. All requested variables entered.
|
|||
b.
Dependent Variable: Gula Post Prandial
|
|||
Model Summary
|
||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.628a
|
.394
|
.370
|
21.629
|
a.
Predictors: (Constant), Indeks Masa tubuh
|
||||
ANOVAb
|
||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
7617.297
|
1
|
7617.297
|
16.282
|
.000a
|
Residual
|
11695.666
|
25
|
467.827
|
|||
Total
|
19312.963
|
26
|
||||
a. Predictors: (Constant), Indeks Masa tubuh
|
||||||
b.
Dependent Variable: Gula Post Prandial
|
||||||
Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
||||
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
1
|
(Constant)
|
48.737
|
23.494
|
2.074
|
.048
|
|
Indeks Masa tubuh
|
4.319
|
1.070
|
.628
|
4.035
|
.000
|
|
a.
Dependent Variable: Gula Post Prandial
|
||||||
Pembuktan Hipotesa:
a. Asumsi : Bahwa model persamaan garis lurus
beserta asumsinya berlaku;
b. Hipotesa : Ho: β1 = 0
Ha : β1 ≠ 0
c. Uji
Statistik : t = 
d. Distribusi
statistik: Bila asumsi terpenuhi dan 
diterima maka uji t digunakan dengan derajat
kebebasan n-1;
diterima maka uji t digunakan dengan derajat
kebebasan n-1;
e. Pengambilan
keputusan: ditolak bila nilai 
lebih besar dari 
= 2,2281
ditolak bila nilai lebih besar dari = 2,2281
f. Perhitungan
statistik: dari komputer output diperoleh besaran nilai 
= 4,319 dan 
= 1,070
= 4,319 dan = 1,070
t=
= 3,956
= 3,956
g. Keputusan
statistik:
Kita menolak Hipotesa nol
h. Kesimpulan:
Slop garis regresi tidak sama dengan 0 maka garis regresi antara IMT dengan GPP
adalah linier.
Latihan 2
Regression
Notes
|
||
Output Created
|
30-Mar-2016 10:13:28
|
|
Comments
|
||
Input
|
Active Dataset
|
DataSet0
|
Filter
|
<none>
|
|
Weight
|
<none>
|
|
Split File
|
<none>
|
|
N of Rows in Working Data File
|
16
|
|
Missing Value Handling
|
Definition of Missing
|
User-defined missing values are treated as missing.
|
Cases Used
|
Statistics are based on cases with no missing values
for any variable used.
|
|
Syntax
|
REGRESSION
/MISSING
LISTWISE
/STATISTICS
COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT
Glukosa
/METHOD=ENTER
BB.
|
|
Resources
|
Processor Time
|
0:00:00.016
|
Elapsed Time
|
0:00:00.282
|
|
Memory Required
|
1356 bytes
|
|
Additional
Memory Required for Residual Plots
|
0 bytes
|
|
[DataSet0]
Variables Entered/Removedb
|
|||
Model
|
Variables Entered
|
Variables Removed
|
Method
|
1
|
Berat Badan (kg)a
|
.
|
Enter
|
a. All requested variables entered.
|
|||
b.
Dependent Variable: Glukosa mg/100ml
|
|||
Model Summary
|
||||
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.484a
|
.234
|
.180
|
9.276
|
a.
Predictors: (Constant), Berat Badan (kg)
|
||||
ANOVAb
|
||||||
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1
|
Regression
|
368.798
|
1
|
368.798
|
4.286
|
.057a
|
Residual
|
1204.639
|
14
|
86.046
|
|||
Total
|
1573.437
|
15
|
||||
a. Predictors: (Constant), Berat Badan (kg)
|
||||||
b.
Dependent Variable: Glukosa mg/100ml
|
||||||
Coefficientsa
|
||||||
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
||||
B
|
Std. Error
|
Beta
|
t
|
Sig.
|
||
1
|
(Constant)
|
61.877
|
19.189
|
3.225
|
.006
|
|
Berat Badan (kg)
|
.510
|
.246
|
.484
|
2.070
|
.057
|
|
a.
Dependent Variable: Glukosa mg/100ml
|
||||||
Pembuktian hipotesa:
a. Asumsi : Bahwa model persamaan garis lurus
beserta asumsinya berlaku;
b. Hipotesa : Ho: β1 = 0
Ha : β1 ≠ 0
c. Uji
Statistik : t =
d. Distribusi
statistik: Bila asumsi terpenuhi dan diterima maka uji t digunakan dengan derajat
kebebasan n-1;
diterima maka uji t digunakan dengan derajat
kebebasan n-1;
e. Pengambilan
keputusan: ditolak bila nilai lebih besar dari = 2,2281
ditolak bila nilai lebih besar dari = 2,2281
f. Perhitungan
statistik: dari komputer output diperoleh besaran nilai =0,51 dan = 0,246
=0,51 dan = 0,246
t=
= 2,073
= 2,073
g. Keputusan
statistik:
Nilai = 2,073 <
=2,2281
= 2,073 <=2,2281
Kita menerima Hipotesa nol
h. Kesimpulan:
Slop garis regresi tidak sama dengan 0 maka garis regresi antara Berat badan
dan Glukosa adalah tidak linier.
i.
Persamaan Garis : Glukosa = 61,877+0,510
BB
