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

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