REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN
/DEPENDENT Y /METHOD=BACKWARD X1 X3 X4 X2 /METHOD=STEPWISE X1 X2 X3
X4 /METHOD=FORWARD X1 X2 X3 X4 /RESIDUALS HIST(ZRESID) NORM(ZRESID).
Regression
Notes
Output Created 13-Jan-2011 10:35:25
Comments
Input Data D:\TUGAS SPSS\DATA SPSS RANI.sav
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data 16
File
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
/DESCRIPTIVES MEAN STDDEV
CORR SIG N
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT Y
/METHOD=BACKWARD X1 X3 X4 X2
/METHOD=STEPWISE X1 X2 X3 X4
/METHOD=FORWARD X1 X2 X3 X4
/RESIDUALS HIST(ZRESID)
NORM(ZRESID).
Resources Processor Time 0:00:00.499
Elapsed Time 0:00:00.514
Memory Required 3444 bytes
Additional Memory Required 632 bytes
for Residual Plots
[DataSet1] D:\TUGAS SPSS\DATA SPSS RANI.sav
Warnings
No variables were entered into the equation
No variables were entered into the equation
Descriptive Statistics
Mean Std. Deviation N
Y 84.00 6.782 16
X1 .25 .447 16
X3 .25 .447 16
X4 75.38 11.529 16
X2 .25 .447 16
Correlations
Y X1 X3 X4 X2
Pearson Correlation Y 1.000 .462 -.088 -.450 -.088
X1 .462 1.000 -.333 .084 -.333
X3 -.088 -.333 1.000 .381 -.333
X4 -.450 .084 .381 1.000 -.459
X2 -.088 -.333 -.333 -.459 1.000
Sig. (1-tailed) Y . .036 .373 .040 .373
X1 .036 . .104 .378 .104
X3 .373 .104 . .072 .104
X4 .040 .378 .072 . .037
X2 .373 .104 .104 .037 .
N Y 16 16 16 16 16
X1 16 16 16 16 16
X3 16 16 16 16 16
X4 16 16 16 16 16
X2 16 16 16 16 16
Variables Entered/Removedb
Variables Variables
Model Entered Removed Method
1 X2, X3, X4, X1a . Enter
2 . X2 Backward
(criterion:
Probability of F-
to-remove >= .
100).
3 . X3 Backward
(criterion:
Probability of F-
to-remove >= .
100).
a. All requested variables entered.
b. Dependent Variable: Y
Model Summaryd
Adjusted R Std. Error of the
Model R R Square Square Estimate
1 .746a .557 .396 5.272
2 .744b .553 .442 5.068
3 .674c .454 .370 5.384
a. Predictors: (Constant), X2, X3, X4, X1
b. Predictors: (Constant), X3, X4, X1
c. Predictors: (Constant), X4, X1
d. Dependent Variable: Y
ANOVAd
Model Sum of Squares df Mean Square F Sig.
1 Regression 384.295 4 96.074 3.457 .046a
Residual 305.705 11 27.791
Total 690.000 15
2 Regression 381.747 3 127.249 4.954 .018b
Residual 308.253 12 25.688
Total 690.000 15
3 Regression 313.140 2 156.570 5.401 .020c
Residual 376.860 13 28.989
Total 690.000 15
a. Predictors: (Constant), X2, X3, X4, X1
b. Predictors: (Constant), X3, X4, X1
c. Predictors: (Constant), X4, X1
d. Dependent Variable: Y
Coefficientsa
Standardized
Unstandardized Coefficients Coefficients
Model B Std. Error Beta t Sig.
1 (Constant) 110.308 10.744 10.267 .000
X1 9.187 3.736 .606 2.459 .032
X3 5.196 3.870 .343 1.343 .206
X4 -.393 .138 -.668 -2.838 .016
X2 -1.187 3.920 -.078 -.303 .768
2 (Constant) 108.796 9.147 11.894 .000
X1 9.702 3.199 .640 3.033 .010
X3 5.636 3.448 .372 1.634 .128
X4 -.380 .127 -.646 -3.001 .011
3 (Constant) 103.929 9.188 11.311 .000
X1 7.628 3.120 .503 2.445 .029
X4 -.290 .121 -.492 -2.394 .032
a. Dependent Variable: Y
Excluded Variablesc
Collinearity
Statistics
Partial
Model Beta In t Sig. Correlation Tolerance
2 X2 -.078a -.303 .768 -.091 .603
3 X2 -.208b -.842 .416 -.236 .702
X3 .372b 1.634 .128 .427 .720
a. Predictors in the Model: (Constant), X3, X4, X1
b. Predictors in the Model: (Constant), X4, X1
c. Dependent Variable: Y
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 77.86 92.73 84.00 4.569 16
Residual -10.146 9.275 .000 5.012 16
Std. Predicted Value -1.345 1.910 .000 1.000 16
Std. Residual -1.884 1.723 .000 .931 16
a. Dependent Variable: Y
Charts
