Novi Dara Utami

7/28/2019 Novi Dara Utami

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Nama : Novi Dara Utami

NIM : 100600018

Grup : A2

Correlations

Notes

Output Created 07-Jun-2013 13:45:10

Comments

Input Active Dataset DataSet0

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Weight

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N of Rows in Working DataFile

30

Missing Value Handling Definition of Missing User-defined missing values are

treated as missing.

Cases Used Statistics for each pair of variables are

based on all the cases with valid data

for that pair.

Syntax CORRELATIONS

/VARIABLES=ohi sex

/PRINT=TWOTAIL NOSIG

/MISSING=PAIRWISE.

Resources Processor Time 0:00:00.016

Elapsed Time 0:00:00.031

Correlations

ohi jenis kelamin

Ohi Pearson Correlation 1 .261

Sig. (2-tailed) .164

N 30 30

jenis kelamin Pearson Correlation .261 1

Sig. (2-tailed) .164

N 30 30

Regression


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Notes


Comments


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30


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

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

/NOORIGIN

/DEPENDENT sex

/METHOD=ENTER ohi

/CASEWISE PLOT(ZRESID) ALL.



Memory Required 1420 bytes

Additional Memory

Required for Residual Plots

0 bytes

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 ohia . Enter

a. All requested variables entered.

b. Dependent Variable: jenis kelamin

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate


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1 .261a .068 .035 .471

a. Predictors: (Constant), ohi


ANOVAb

Model

Sum of

Squares df Mean Square F Sig.

1 Regression .454 1 .454 2.047 .164a

Residual 6.212 28 .222

Total 6.667 29

a. Predictors: (Constant), ohi


Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

B Std. Error Beta t Sig.

1 (Constant) 1.039 .223 4.660 .000

ohi .306 .214 .261 1.431 .164a. Dependent Variable: jenis kelamin

Casewise Diagnosticsa

Case

Numb

er Std. Residual jenis kelamin

Predicted

Value Residual

1 1.178 2 1.45 .555

2 -.621 1 1.29 -.293

3 -.621 1 1.29 -.293

4 -.621 1 1.29 -.293

5 -.731 1 1.34 -.345

6 -.731 1 1.34 -.345


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7 -1.160 1 1.55 -.546

8 -.511 1 1.24 -.241

9 1.178 2 1.45 .555

10 1.184 2 1.44 .558

11 -.621 1 1.29 -.293

12 -.297 1 1.14 -.140

13 .963 2 1.55 .454

14 1.392 2 1.34 .655

15 1.184 2 1.44 .558

16 1.716 2 1.19 .808

17 1.392 2 1.34 .655

18 1.392 2 1.34 .655

19 -.731 1 1.34 -.345

20 -.731 1 1.34 -.345

21 -.083 1 1.04 -.039

22 -.731 1 1.34 -.345

23 1.612 2 1.24 .759

24 -.731 1 1.34 -.345

25 -.621 1 1.29 -.293

26 -.083 1 1.04 -.039

27 -.731 1 1.34 -.345

28 -.939 1 1.44 -.442

29 -.731 1 1.34 -.345

30 -1.160 1 1.55 -.546

a. Dependent Variable: jenis kelamin

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 1.04 1.55 1.33 .125 30

Residual -.546 .808 .000 .463 30

Std. Predicted Value -2.352 1.701 .000 1.000 30

Std. Residual -1.160 1.716 .000 .983 30

a. Dependent Variable: jenis kelamin

Crosstabs

Notes



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treated as missing.

Cases Used Statistics for each table are based on

all the cases with valid data in the

specified range(s) for all variables in

each table.

Syntax CROSSTABS/TABLES=sex BY ohi

/FORMAT=AVALUE TABLES

/STATISTICS=CHISQ CC

/CELLS=COUNT

/COUNT ROUND CELL.



Dimensions Requested 2Cells Available 174762

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

jenis kelamin * ohi 30 100.0% 0 .0% 30 100.0%

jenis kelamin * ohi Crosstabulation

Count

ohi

0 0 0 1 1 1

jenis kelamin laki-laki 2 1 0 1 5 8

perempuan 0 0 1 1 0 3

Total 2 1 1 2 5 11


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jenis kelamin * ohi Crosstabulation

Count

ohi

1 1 2 Total

jenis kelamin laki-laki 1 0 2 20

perempuan 2 2 1 10

Total 3 2 3 30

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 11.932a 8 .154

Likelihood Ratio 14.889 8 .061

Linear-by-Linear

Association

1.976 1 .160

N of Valid Cases 30

a. 17 cells (94,4%) have expected count less than 5. The minimum

expected count is ,33.

Symmetric Measures

Value Approx. Sig.

Nominal by Nominal Contingency Coefficient .533 .154

N of Valid Cases 30

Curve Fit

Notes


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treated as missing.

Cases Used Cases with a missing value in any

variable are not used in the analysis.

Syntax CURVEFIT

/VARIABLES=sex WITH ohi

/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 LagsPer Cross-Correlation Plots

MXCROSS = 7

Maximum Number of New

Variables Generated Per

Procedure

MXNEWVAR = 60

Maximum Number of New

Cases Per Procedure

MXPREDICT = 1000

Treatment of User-Missing

Values

MISSING = EXCLUDE

Confidence Interval

Percentage Value

CIN = 95

Tolerance for Entering

Variables in Regression

Equations

TOLER = ,0001

Maximum Iterative

Parameter Change

CNVERGE = ,001

Method of Calculating Std.

Errors for Autocorrelations

ACFSE = IND

Length of Seasonal Period Unspecified


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Variable Whose Values

Label Observations in Plots

Unspecified

Equations Include CONSTANT

Model Description

Model Name MOD_2

Dependent Variable 1 jenis kelamin

Equation 1 Linear

Independent Variable ohi

Constant Included

Variable Whose Values

Label Observations in Plots

Unspecified

Case Processing Summary

N

Total Cases 30

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

jenis kelamin ohi

Number of Positive Values 30 28

Number of Zeros 0 2

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:jenis kelamin

Equati

on

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .068 2.047 1 28 .164 1.039 .306

The independent variable is ohi.

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