data regresi linier
DESCRIPTION
jhjhTRANSCRIPT
LAMPIRANREGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA COLLIN TOL /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT X /METHOD=ENTER Y /RESIDUALS DURBIN NORM(ZRESID) /SAVE RESID SDRESID.
Data InputX Y RES_1 SDR_1
18.5 120 1.24201 0.6213731.7 66 3.73837 1.33412
25.9 74 -0.4759-
0.1410129.1 64 0.74194 0.2317930.2 76 4.22053 1.49432
24.65 62-
4.10449-
1.59077
21.35 82-
3.44018-
1.13068
19.3 100 -1.9223-
0.63691
Regression
Notes
Output Created 28-Oct-2015 19:07:54
Comments
Input Active Dataset DataSet0
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File
8
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
COLLIN TOL
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT X
/METHOD=ENTER Y
/RESIDUALS DURBIN
NORM(ZRESID)
/SAVE RESID SDRESID.
Resources Processor Time 0:00:02.418
Elapsed Time 0:00:02.982
Memory Required 1356 bytes
Additional Memory Required
for Residual Plots
312 bytes
Variables Created or
Modified
RES_1 Unstandardized Residual
SDR_1 Studentized Deleted Residual
[DataSet0]
Variables Entered/Removedb
Model
Variables
Entered
Variables
Removed Method
1 Ya . Enter
a. All requested variables entered.
b. Dependent Variable: X
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .791a .626 .563 3.32878 1.649
a. Predictors: (Constant), Y
b. Dependent Variable: X
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 111.189 1 111.189 10.034 .019a
Residual 66.485 6 11.081
Total 177.674 7
a. Predictors: (Constant), Y
b. Dependent Variable: X
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
B Std. Error Beta t Sig.
1 (Constant) 41.044 5.173 7.934 .000
Y -.198 .063 -.791 -3.168 .019
a. Dependent Variable: X
Coefficientsa
Model
Collinearity Statistics
Tolerance VIF
1 Y 1.000 1.000
a. Dependent Variable: X
Collinearity Diagnosticsa
Model
Dimensi
on
Variance Proportions
Eigenvalue Condition Index (Constant) Y
1 1 1.974 1.000 .01 .01
2 .026 8.675 .99 .99
a. Dependent Variable: X
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 17.2580 28.7545 25.0875 3.98549 8
Std. Predicted Value -1.965 .920 .000 1.000 8
Standard Error of Predicted
Value
1.181 2.738 1.596 .503 8
Adjusted Predicted Value 14.6628 30.0932 24.8631 4.76033 8
Residual -4.10449 4.22053 .00000 3.08185 8
Std. Residual -1.233 1.268 .000 .926 8
Stud. Residual -1.420 1.361 .022 1.044 8
Deleted Residual -5.44316 4.86323 .22435 4.01488 8
Stud. Deleted Residual -1.591 1.494 .023 1.114 8
Mahal. Distance .006 3.859 .875 1.260 8
Cook's Distance .002 .449 .162 .157 8
Centered Leverage Value .001 .551 .125 .180 8
a. Dependent Variable: X
Charts