Nama: Anjan Setyo WahyudiNIM: 24010212130055Praktikum ADK 1

VII. OUTPUT :

LOGISTIC REGRESSION VARIABLES y /METHOD=ENTER x /PRINT=GOODFIT ITER(1) /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

Logistic RegressionNotesOutput Created27-NOV-2014 23:22:25Comments

InputDataI:\adk1.sav

Active DatasetDataSet1

Filter

Weight

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N of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missingSyntaxLOGISTIC REGRESSION VARIABLES y /METHOD=ENTER x /PRINT=GOODFIT ITER(1) /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).ResourcesProcessor Time00:00:00.02

Elapsed Time00:00:00.17

[DataSet1] I:\adk1.sav

Case Processing SummaryUnweighted CasesaNPercentSelected CasesIncluded in Analysis100100.0

Missing Cases0.0

Total100100.0Unselected Cases0.0Total100100.0

a. If weight is in effect, see classification table for the total number of cases.

Dependent Variable EncodingOriginal ValueInternal Value0011

Block 0: Beginning Block

Iteration Historya,b,cIteration-2 Log likelihoodCoefficients

ConstantStep 01123.855-.760

2123.820-.800

3123.820-.800

a. Constant is included in the model.b. Initial -2 Log Likelihood: 123.820c. Estimation terminated at iteration number 3 because parameter estimates changed by less than .001.

Classification Tablea,b

ObservedPredicted

yPercentage Correct

01

Step 0y0690100.0

1310.0

Overall Percentage

69.0

a. Constant is included in the model.b. The cut value is .500

Variables in the Equation

BS.E.WalddfSig.Exp(B)Step 0Constant-.800.21613.6941.000.449

Variables not in the Equation

ScoredfSig.Step 0Variablesx26.2021.000

Overall Statistics26.2021.000

Block 1: Method = EnterIteration Historya,b,c,dIteration-2 Log likelihoodCoefficients

ConstantxStep 1198.747-2.660.038

297.009-3.407.050

396.963-3.551.053

496.963-3.556.053

596.963-3.556.053

a. Method: Enterb. Constant is included in the model.c. Initial -2 Log Likelihood: 123.820d. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Omnibus Tests of Model Coefficients

Chi-squaredfSig.Step 1Step26.8571.000

Block26.8571.000

Model26.8571.000

Model SummaryStep-2 Log likelihoodCox & Snell R SquareNagelkerke R Square196.963a.236.332

a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Hosmer and Lemeshow TestStepChi-squaredfSig.16.3318.610

Contingency Table for Hosmer and Lemeshow Test

y = 0y = 1Total

ObservedExpectedObservedExpected

Step 1188.88521.11510

287.89011.1109

31211.27111.72913

477.66521.3359

598.13211.86810

665.39111.6097

787.10422.89610

857.39285.60813

944.42465.57610

102.84778.1539

Classification Tablea

ObservedPredicted

yPercentage Correct

01

Step 1y063691.3

1181341.9

Overall Percentage

76.0

a. The cut value is .500

Variables in the Equation

BS.E.WalddfSig.Exp(B)Step 1ax.053.01316.3731.0001.055

Constant-3.556.71724.6061.000.029

a. Variable(s) entered on step 1: x.