Mar 16, 2014 - SOAL: Diketahui: Data Sebagai Berikut⦠NO Tinggi Badan ( cm ) X Berat Badan ( KG ) Y 1 168 63 2 173 81 ...
SOAL: Diketahui: Data Sebagai Berikut…
NO 1 2 3 4 5 6 7 8 9 10
Tinggi Badan ( cm ) X 168 173 162 157 160 165 163 170 168 164
Berat Badan ( KG ) Y 63 81 54 49 52 62 56 78 64 61
Ditanya: -Tentukan Nilai Koefisien Korelasi dan Regresi -Apakah Nilai Koefisien Signifikan atau Tidak Jawab: -Nilai Koefisien Korelasi dan Regresin Menggunakan SPSS REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X.
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Regression Notes
Output Created
15-Mar-2014 22:56:04
Comments Input
Active Dataset
DataSet1
Filter
Weight
Split File
N of Rows in Working Data
10
File Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
Page 1
Cases Used
Statistics are based on cases with no missing values for any variable used.
Syntax
REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Y /METHOD=ENTER X.
Resources
Processor Time
00:00:00.156
Elapsed Time
00:00:00.100
Memory Required
1372 bytes
Additional Memory Required
0 bytes
for Residual Plots
[DataSet1] Descriptive Statistics Mean
Std. Deviation
N
Y
62.00
10.499
10
X
165.00
4.830
10
Correlations Y Pearson Correlation
Sig. (1-tailed)
N
X
Y
1.000
.946
X
.946
1.000
Y
.
.000
X
.000
.
Y
10
10
X
10
10
FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
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Variables Entered/Removed
b
Variables Model
Variables Entered
1
X
Removed
a
Method . Enter
a. All requested variables entered. b. Dependent Variable: Y
Model Summary
Model
R
Std. Error of the
Square
Estimate
R Square a
1
Adjusted R
.946
.896
.883
Change Statistics R Square Change
3.594
F Change
.896
df1
68.814
df2 1
Sig. F Change 8
.000
a. Predictors: (Constant), X
b
ANOVA Model 1
Sum of Squares
df
Mean Square
Regression
888.686
1
888.686
Residual
103.314
8
12.914
Total
992.000
9
F
Sig. a
68.814
.000
a. Predictors: (Constant), X b. Dependent Variable: Y
Coefficients
a
Standardized Unstandardized Coefficients Model 1
B (Constant) X
a.
Std. Error
-277.429
40.933
2.057
.248
Coefficients Beta
95% Confidence Interval for B t
.946
Sig.
Lower Bound
Upper Bound
-6.778
.000
-371.821
-183.036
8.295
.000
1.485
2.629
Dependent Variable: Y
FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
Page 3
CORRELATIONS /VARIABLES=X Y /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.
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Correlations Notes
Output Created
16-Mar-2014 01:00:09
Comments Input
Active Dataset
DataSet1
Filter
Weight
Split File
N of Rows in Working Data
10
File Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics for each pair of variables are based on all the cases with valid data for that pair.
Syntax
CORRELATIONS /VARIABLES=X Y /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.
Resources
Processor Time
00:00:00.032
Elapsed Time
00:00:00.023
[DataSet1] Correlations X X
Pearson Correlation
Y 1
Sig. (2-tailed) N Y
Pearson Correlation Sig. (2-tailed) N
**
.946
.000 10
10
**
1
.946
.000 10
10
**. Correlation is significant at the 0.01 level (2-tailed).
FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
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Untuk Penghitungan Manual Sebagai Berikut: -
Nilai Koefisien Korelasi
NO Xi Yi Xi² Yi² Xi.Yi 1 168 63 28224 3969 10584 2 173 81 29929 6561 14013 3 162 54 26244 2916 8748 4 157 49 24649 2401 7693 5 160 52 25600 2704 8320 6 165 62 27225 3844 10230 7 163 56 26569 3136 9128 8 170 78 28900 6084 13260 9 168 64 28224 4096 10752 10 164 61 26896 3721 10004 Jumlah 1650 620 272460 39432 102732 Ket: x adalah Tinggi Badan Y adalah Berat Badan
Berdasarkan Tingkat Hubungan Nilai r Maka: “Terdapat Hubungan Korelasi Yang Sangat Kuat Antara Tinggi Badan dan Berat Badan Dengan Arah Positif” FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
Page 5
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Hipotesis Statistik
Ho: ρxy = 0 (Tidak terdapat hubungan antara tinggi badan dan berat badan) H1: ρxy ≠ 0 (Terdapat hubungan antara tinggi badan dan berat badan)
Dari tabel t dengan α = 0,05 Diperoleh ttab = t0.025;df=8 = 2,306 Kriteria uji: Karena
( ) α = 0,025 dan df = n-2
df = 10 – 2 = 8
= 8,295> ttab = 2,306 maka Ho ditolak
Kesimpulan: “Bahwa Berat Badan Berpengaruh Signifikan Terhadap Berat Badan”.
FRANDIKA SEPTA (TUGAS REGRESI DAN KORELASI MENGGUNAKAN SPSS)
[email protected] || http://www.frandika-septa.blogspot.com
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