regresi maloklusi
Post on 11-Dec-2015
7 Views
Preview:
DESCRIPTION
TRANSCRIPT
Notes
Output Created 03-SEP-2015 10:02:41
Comments
Input Active Dataset DataSet0
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 30
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
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT Diagnostic
/METHOD=ENTER Maloklusi.
Resources Processor Time 00:00:00.02
Elapsed Time 00:00:00.26
Memory Required 1356 bytes
Additional Memory Required for
Residual Plots0 bytes
[DataSet0]
Variables Entered/Removeda
Model Variables Entered
Variables
Removed Method
1 Maloklusib . Enter
a. Dependent Variable: Diagnostic
b. All requested variables entered.
Model Summary
Model R R Square Adjusted R Square
Std. Error of the
Estimate
1 .503a .253 .227 2.21034
a. Predictors: (Constant), Maloklusi
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 46.403 1 46.403 9.498 .005b
Residual 136.797 28 4.886
Total 183.200 29
a. Dependent Variable: Diagnostic
b. Predictors: (Constant), Maloklusi
Coefficientsa
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) .822 .929 .885 .384
Maloklusi .992 .322 .503 3.082 .005
a. Dependent Variable: Diagnostic
top related