olahan no 1-2

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FREQUENCIES VARIABLES=X1 Y

/NTILES=4

/STATISTICS=STDDEV MEAN MEDIAN MODE SUM SKEWNESS SESKEW KURTOSIS SEKURT

/BARCHART FREQ

/ORDER=ANALYSIS.

Frequencies

Notes

Output Created 21-Dec-2011 14:06:15

Comments

Input Data D:\Tugas Akhir dikumpulkan\Statistik

SPSS\data SPSS.sav

Active Dataset DataSet1

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 11

Missing Value Handl ing Def init ion of Missing User-def ined missing values are treated as

missing.

Cases Used Statistics are based on all cases with valid

data.

Syntax FREQUENCIES VARIABLES=X1 Y

/NTILES=4

/STATISTICS=STDDEV MEAN MEDIAN

MODE SUM SKEWNESS SESKEW

KURTOSIS SEKURT

/BARCHART FREQ

/ORDER=ANALYSIS.

Resources Processor Time 00:00:01.388

Elapsed Time 00:00:01.457

[DataSet1] D:\Tugas Akhir dikumpulkan\Statistik SPSS\data SPSS.sav

Statistics

X1 Y

N Valid 11 11

Missing 0 0

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Mean 1223.45 117.36

Median 937.00 81.00

Mode 183a 37a

Std. Deviation 1.019E3 107.642

Skewness .906 2.290

Std. Error of Skewness .661 .661

Kurtosis -.089 6.043

Std. Error of Kurtosis 1.279 1.279

Sum 13458 1291

Percentiles 25 320.00 42.00

50 937.00 81.00

75 2006.00 152.00

a. Multiple modes exist. The smallest value is shown

Frequency Table

X1

Frequency Percent Valid P ercent

Cumulative

Percent

Valid 183 1 9.1 9.1 9.1

250 1 9.1 9.1 18.2

320 1 9.1 9.1 27.3

474 1 9.1 9.1 36.4

669 1 9.1 9.1 45.5

937 1 9.1 9.1 54.5

1250 1 9.1 9.1 63.6

1602 1 9.1 9.1 72.7

2006 1 9.1 9.1 81.8

2488 1 9.1 9.1 90.9

3279 1 9.1 9.1 100.0

Total 11 100.0 100.0

Y


Cumulative

Percent

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Valid 37 1 9.1 9.1 9.1

40 1 9.1 9.1 18.2

42 1 9.1 9.1 27.3

49 1 9.1 9.1 36.4

76 1 9.1 9.1 45.5

81 1 9.1 9.1 54.5

98 1 9.1 9.1 63.6

141 1 9.1 9.1 72.7

152 1 9.1 9.1 81.8

165 1 9.1 9.1 90.9

410 1 9.1 9.1 100.0

Total 11 100.0 100.0

Bar Chart

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REGRESSION

/DESCRIPTIVES MEAN STDDEV CORR SIG N

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA COLLIN TOL CHANGE ZPP

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT Y

/METHOD=ENTER X1

/SCATTERPLOT=(*SRESID ,*ZPRED)

/RESIDUALS DURBIN HIST(ZRESID) NORM(ZRESID).

Regression

Notes


Comments


SPSS\data SPSS.sav


Filter <none>

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Weight <none>

Split File <none>



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

COLLIN TOL CHANGE ZPP


/NOORIGIN

/DEPENDENT Y

/METHOD=ENTER X1


/RESIDUALS DURBIN HIST(ZRESID)

NORM(ZRESID).



Memory Required 1468 bytes

Additional Memory Required for

Residual Plots912 bytes

[DataSet1] D:\Tugas Akhir dikumpulkan\Statistik SPSS\data SPSS.sav

Descriptive Statistics

Mean Std. Deviation N

Y 98.73 58.389 11

X1 1223.45 1018.738 11

Correlations

Y X1

Pearson Correlation Y 1.000 .987

X1 .987 1.000

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Sig. (1-tailed) Y . .000

X1 .000 .

N Y 11 11

X1 11 11

Variables Entered/Removedb

Model Variables EnteredVariablesRemoved Method

1 X1a . Enter

a. All requested variables entered.

b. Dependent Variable: Y

Model Summaryb

Model R R Square Adjusted R Square

Std. Error of the

Estimate Change Statistics Durbin-Watson

R Square Change F Change df1 df2 Sig. F Change

1 .987a .975 .972 9.711 .975 352.530 1 9 .000 1.527

a. Predictors: (Constant), X1


ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 33243.485 1 33243.485 352.530 .000a

Residual 848.697 9 94.300

Total 34092.182 10

a. Predictors: (Constant), X1


Coefficients a

Model Unstandardized Coefficients

Standardized

Coefficients t Sig. Correlations Collinearity Statistics

B Std. Error Beta Zero-order Partial Part Tolerance VIF

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1 (Constant) 29.484 4.709 6.261 .000

X1 .057 .003 .987 18.776 .000 .987 .987 .987 1.000 1.000

a. Dependent Variable: Y

Collinearity Diagnosticsa

Model

Dimensi

on Eigenvalue Condition Index Variance Proportions

(Constant) X1

1 1 1.783 1.000 .11 .11

2 .217 2.868 .89 .89


Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 39.84 215.06 98.73 57.657 11

Std. Predicted Value -1.021 2.018 .000 1.000 11

Standard Error of Predicted

Value2.929 6.853 4.004 1.105 11

Adjusted Predicted Value 40.53 225.05 99.70 59.464 11

Residual -10.064 20.848 .000 9.212 11

Std. Residual -1.036 2.147 .000 .949 11

Stud. Residual -1.463 2.269 -.042 1.058 11

Deleted Residual -20.050 23.287 -.975 11.720 11

Stud. Deleted Residual -1.580 3.270 .048 1.303 11

Mahal. Distance .001 4.071 .909 1.147 11

Cook's Distance .001 1.062 .157 .312 11

Centered Leverage Value .000 .407 .091 .115 11


Charts

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SAVE OUTFILE='D:\Tugas Akhir dikumpulkan\Statistik SPSS\SPSS bener\data no 1.sav'

/COMPRESSED.

NEW FILE.

DATASET NAME DataSet2 WINDOW=FRONT.

FREQUENCIES VARIABLES=X1 X2 Y

/NTILES=4

/STATISTICS=STDDEV MEAN MEDIAN MODE KURTOSIS SEKURT

/HISTOGRAM NORMAL

/ORDER=ANALYSIS.

Frequencies

Notes


Comments

Input Active Dataset DataSet2

Filter <none>

Weight <none>

Split File <none>


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missing.

Cases Used Statistics are based on all cases with valid

data.

Syntax FREQUENCIES VARIABLES=X1 X2 Y

/NTILES=4

/STATISTICS=STDDEV MEAN MEDIAN

MODE KURTOSIS SEKURT

/HISTOGRAM NORMAL

/ORDER=ANALYSIS.



[DataSet2]

Statistics

X1 X2 Y

N Valid 11 11 10

Missing 0 0 1

Mean 1223.45 196.45 90.10

Median 937.00 163.00 78.50

Mode 183a 57a 40a

Std. Deviation 1.019E3 118.649 47.123

Kurtosis -.089 -1.014 -1.302

Std. Error of Kurtosis 1.279 1.279 1.334

Percentiles 25 320.00 84.00 47.25

50 937.00 163.00 78.50

75 2006.00 304.00 143.75

a. Multiple modes exist. The smallest value is shown

Frequency Table

X1


Cumulative

Percent

Valid 183 1 9.1 9.1 9.1

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250 1 9.1 9.1 18.2

320 1 9.1 9.1 27.3

474 1 9.1 9.1 36.4

669 1 9.1 9.1 45.5

937 1 9.1 9.1 54.5

1250 1 9.1 9.1 63.6

1602 1 9.1 9.1 72.7

2006 1 9.1 9.1 81.8

2488 1 9.1 9.1 90.9

3279 1 9.1 9.1 100.0

Total 11 100.0 100.0

X2


Cumulative

Percent

Valid 57 1 9.1 9.1 9.1

81 1 9.1 9.1 18.2

84 1 9.1 9.1 27.3

99 1 9.1 9.1 36.4

152 1 9.1 9.1 45.5

163 1 9.1 9.1 54.5

197 1 9.1 9.1 63.6

283 1 9.1 9.1 72.7

304 1 9.1 9.1 81.8

331 1 9.1 9.1 90.9

410 1 9.1 9.1 100.0

Total 11 100.0 100.0

Y


Cumulative

Percent

Valid 40 1 9.1 10.0 10.0

42 1 9.1 10.0 20.0

49 1 9.1 10.0 30.0

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57 1 9.1 10.0 40.0

76 1 9.1 10.0 50.0

81 1 9.1 10.0 60.0

98 1 9.1 10.0 70.0

141 1 9.1 10.0 80.0

152 1 9.1 10.0 90.0

165 1 9.1 10.0 100.0

Total 10 90.9 100.0

Missing System 1 9.1

Total 11 100.0

Histogram

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REGRESSION

/DESCRIPTIVES MEAN STDDEV CORR SIG N

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA COLLIN TOL CHANGE ZPP


/NOORIGIN

/DEPENDENT Y

/METHOD=ENTER X1 X2


/RESIDUALS DURBIN HIST(ZRESID) NORM(ZRESID).

Regression

Notes


Comments


Filter <none>

Weight <none>

Split File <none>

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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

COLLIN TOL CHANGE ZPP


/NOORIGIN

/DEPENDENT Y

/METHOD=ENTER X1 X2


/RESIDUALS DURBIN HIST(ZRESID)

NORM(ZRESID).



Memory Required 1636 bytes

Additional Memory Required for

Residual Plots904 bytes

[DataSet2]


Mean Std. Deviation N

Y 100.55 56.557 11

X1 1223.45 1018.738 11

X2 196.45 118.649 11

Correlations

Y X1 X2

Pearson Correlation Y 1.000 .983 .990

X1 .983 1.000 .986

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Model Unstandardized Coefficients

Standardized

Coefficients t Sig. Correlations Collinearity Statistics

B Std. Error Beta Zero-order Partial Part Tolerance VIF

1 (Constant) 14.138 8.772 1.612 .146

X1 .014 .016 .257 .888 .401 .983 .299 .042 .027 36.753

X2 .351 .138 .736 2.538 .035 .990 .668 .121 .027 36.753


Collinearity Diagnosticsa

Model

Dimensi

on Eigenvalue Condition Index Variance Proportions

(Constant) X1 X2

1 1 2.759 1.000 .01 .00 .00

2 .237 3.412 .24 .01 .00

3 .004 26.244 .75 .99 1.00


Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 36.75 204.84 100.55 56.037 11

Std. Predicted Value -1.138 1.861 .000 1.000 11

Standard Error of Predicted

Value2.603 6.796 4.278 1.349 11

Adjusted Predicted Value 28.11 204.56 99.58 56.190 11

Residual -7.129 20.249 .000 7.652 11

Std. Residual -.833 2.367 .000 .894 11

Stud. Residual -.935 2.827 .046 1.061 11

Deleted Residual -8.969 28.885 .965 10.875 11

Stud. Deleted Residual -.926 84.490 7.476 25.548 11

Mahal. Distance .017 5.402 1.818 1.784 11

Cook's Distance .001 1.136 .152 .342 11

Centered Leverage Value .002 .540 .182 .178 11


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Charts

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NPAR TESTS

/K-S(NORMAL)=X1 X2 Y

/STATISTICS DESCRIPTIVES

/MISSING ANALYSIS.

NPar Tests

Notes


Comments


Filter <none>

Weight <none>

Split File <none>



missing.

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Cases Used Statistics for each test are based on all

cases with valid data for the variable(s)

used in that test.

Syntax NPAR TESTS

/K-S(NORMAL)=X1 X2 Y

/STATISTICS DESCRIPTIVES

/MISSING ANALYSIS.



Number of Cases Alloweda 131072

a. Based on availability of workspace memory.

[DataSet2]


N Mean Std. Deviation Minimum Maximum

X1 11 1223.45 1018.738 183 3279

X2 11 196.45 118.649 57 410

Y 11 100.55 56.557 40 205

One-Sample Kolmogorov-Smirnov Test

X1 X2 Y

N 11 11 11

Normal Parametersa Mean 1223.45 196.45 100.55

Std. Deviation 1.019E3 118.649 56.557

Most Extreme Differences Absolute .161 .158 .181

Positive .161 .158 .181

Negative -.154 -.131 -.142

Kolmogorov-Smirnov Z .535 .524 .599

Asymp. Sig. (2-tailed) .937 .947 .866

a. Test distribution is Normal.

DATASET ACTIVATE DataSet2.

DATASET CLOSE DataSet1.

SAVE OUTFILE='D:\Tugas Akhir dikumpulkan\Statistik SPSS\SPSS bener\no 2.sav'

/COMPRESSED

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/COMPRESSED.

* Curve Estimation.

TSET NEWVAR=NONE.

CURVEFIT

/VARIABLES=Y WITH X1

/CONSTANT

/MODEL=LINEAR

/PLOT FIT.

Curve Fit

Notes


Comments


SPSS\SPSS bener

o 2.sav


Filter <none>

Weight <none>

Split File <none>


Mi ss ing Val ue Hand li ng Defi ni tion of Missing User-de fined missi ng va lues are tr ea ted as

missing.

Cases Used Cases with a missing value in any variable

are not used in the analysis.

Syntax CURVEFIT


/CONSTANT

/MODEL=LINEAR

/PLOT FIT.



Use From First observation

To Last observation

Predict From First Observation following the use period

To Last observation

Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

Saving New Variables NEWVAR = NONE

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Maximum Number of Lags in

Autocorrelation or Partial

Autocorrelation Plots

MXAUTO = 16

Maximum Number of Lags Per

Cross-Correlation PlotsMXCROSS = 7

Maximum Number of New

Variables Generated Per

Procedure

MXNEWVAR = 60


Cases Per Procedure MXPREDICT = 1000

Treatment of User-Missing

ValuesMISSING = EXCLUDE

Confidence Interval Percentage

ValueCIN = 95

Tolerance for Entering Variables

in Regression EquationsTOLER = .0001

Maximum Iterative Parameter

ChangeCNVERGE = .001

Method of Calculating Std.

Errors for AutocorrelationsACFSE = IND

Length of Seasonal Period Unspecified

Variable Whose Values Label

Observations in PlotsUnspecified

Equations Include CONSTANT

[DataSet2] D:\Tugas Akhir dikumpulkan\Statistik SPSS\SPSS bener\no 2.sav

Model Description

Model Name MOD_1

Dependent Variable 1 Y

Equation 1 Linear

Independent Variable X1

Constant Included

Variable Whose Values Label Observations in Plots Unspecified

Case Processing Summary

N

T l C 11

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Total Cases 11

Excluded Casesa 0

Forecasted Cases 0

Newly Created Cases 0

a. Cases with a missing value in any

variable are excluded from the analysis.

Variable Processing Summary

Variables

Dependent Independent

Y X1

Number of Positive Values 11 11

Number of Zeros 0 0

Number of Negative Values 0 0

Number of Missing Values User-Missing 0 0

System-Missing 0 0

Model Summary and Parameter Estimates

Dependent Variable:Y

Equation Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .967 263.364 1 9 .000 33.755 .055

The independent variable is X1.

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* Curve Estimation.

TSET NEWVAR=NONE.

CURVEFIT


/CONSTANT

/MODEL=LINEAR

/PLOT FIT.

Curve Fit

Notes


Comments


SPSS\SPSS bener

o 2.sav


Filter <none>

Weight <none>

Split File <none>

8/3/2019 olahan no 1-2


Split File <none>


Mi ss ing Val ue Hand li ng Defi ni tion of Missing User-de fined missi ng va lues are tr ea ted as

missing.

Cases Used Cases with a missing value in any variable

are not used in the analysis.

Syntax CURVEFIT


/CONSTANT

/MODEL=LINEAR

/PLOT FIT.



Use From First observation

To Last observation

Predict From First Observation following the use period

To Last observation

Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

Saving New Variables NEWVAR = NONE

Maximum Number of Lags in

Autocorrelation or Partial

Autocorrelation Plots

MXAUTO = 16

Maximum Number of Lags Per

Cross-Correlation PlotsMXCROSS = 7


Variables Generated Per

Procedure

MXNEWVAR = 60


Cases Per ProcedureMXPREDICT = 1000

Treatment of User-Missing

ValuesMISSING = EXCLUDE

Confidence Interval Percentage

ValueCIN = 95

Tolerance for Entering Variables

in Regression EquationsTOLER = .0001

Maximum Iterative Parameter

ChangeCNVERGE = .001

Method of Calculating Std.

Errors for AutocorrelationsACFSE = IND


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Variable Whose Values Label

Observations in PlotsUnspecified

Equations Include CONSTANT

[DataSet2] D:\Tugas Akhir dikumpulkan\Statistik SPSS\SPSS bener\no 2.sav

Model Description

Model Name MOD_2

Dependent Variable 1 Y

Equation 1 Linear

Independent Variable X2

Constant Included

Variable Whose Values Label Observations in Plots Unspecified

Case Processing Summary

N

Total Cases 11

Excluded Casesa 0

Forecasted Cases 0

Newly Created Cases 0

a. Cases with a missing value in any

variable are excluded from the analysis.

Variable Processing Summary

Variables

Dependent Independent

Y X2

Number of Positive Values 11 11

Number of Zeros 0 0

Number of Negative Values 0 0

Number of Missing Values User-Missing 0 0

System-Missing 0 0

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Model Summary and Parameter Estimates

Dependent Variable:Y

Equation Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .980 438.627 1 9 .000 7.847 .472

The independent variable is X2.

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