partial corr matrix = in ( * ) / variables = exercise …correlations control variables stress...
TRANSCRIPT
comment recursive path model of illness, figure 7.5, table 4.2. comment model diagram with ols estimates in figure 11.1.
comment observed means are 40.90 0.0 67.10 4.80 716.70.
comment but this model has no mean structure.
matrix data variables = exercise hardiness fitness stress illness/contents=mea
n sd n corr
/format=lower nodiagonal.
begin data
0 0 0 0 0
66.50 38.00 18.40 33.50 62.48
373 373 373 373 373
-.03
.39 .07
-.05 -.23 -.13
-.08 -.16 -.29 .34
end data.
comment vanishing partial correlations for conditional independences of a basi
s set.
partial corr matrix=in(*)/variables = exercise with stress by hardiness (1).
Partial Corr
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = exercise with stress by hardiness (1).
00:00:00.02
00:00:00.00
Page 1
Correlations
Control Variables stress
hardiness exercise Correlation
Significance (2-tailed)
df
-.058
.260
370
partial corr matrix=in(*)/variables = exercise with illness by fitness, stress
(2).
Partial Corr
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = exercise with illness by fitness, stress (2).
00:00:00.00
00:00:00.00
Correlations
Control Variables illness
fitness & stress exercise Correlation
Significance (2-tailed)
df
.039
.450
369
partial corr matrix=in(*)/variables = hardiness with fitness by exercise (1).
Partial Corr
Page 2
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = hardiness with fitness by exercise (1).
00:00:00.00
00:00:00.00
Correlations
Control Variables fitness
exercise hardiness Correlation
Significance (2-tailed)
df
.089
.087
370
partial corr matrix=in(*)/variables = hardiness with illness by fitness, stres
s (2).
Partial Corr
Page 3
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = hardiness with illness by fitness, stress (2).
00:00:00.00
00:00:00.00
Correlations
Control Variables illness
fitness & stress hardiness Correlation
Significance (2-tailed)
df
-.081
.118
369
partial corr matrix=in(*)/variables = fitness with stress by exercise, hardine
ss (2).
Partial Corr
Page 4
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User defined missing values are treated as missing.Statistics are based on cases with no missing data for any variable listed.partial corr matrix=in(*)/variables = fitness with stress by exercise, hardiness (2).
00:00:00.00
00:00:00.00
Correlations
Control Variables stress
exercise & hardiness fitness Correlation
Significance (2-tailed)
df
-.103
.048
369
comment estimates of unanalyzed association between exrercise and hardiness.
regression matrix=in(*)/variables=exercise,hardiness/dependent=hardiness/metho
d=enter/descriptives=cov corr.
Regression
Page 5
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,hardiness/dependent=hardiness/method=enter/descriptives=cov corr.
00:00:00.00
00:00:00.01
4448 bytes
0 bytes
Correlations
exercise hardiness
Pearson Correlation exercise
hardiness
Covariance exercise
hardiness
1.000 -.030
-.030 1.000
4422.250 -75.810
-75.810 1444.000
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 exerciseb . Enter
Dependent Variable: hardinessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .030a .001 -.002 38.0340516
Predictors: (Constant), exercisea.
Page 6
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
483.451 1 483.451 .334 .564b
536684.549 371 1446.589
537168.000 372
Dependent Variable: hardinessa.
Predictors: (Constant), exerciseb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
exercise
.000 1.969 .000 1.000
-.017 .030 -.030 -.578 .564
Dependent Variable: hardinessa.
comment direct efects of exercise on fitness and of hardiness on stress.
regression matrix=in(*)/variables=exercise,fitness/dependent=fitness/method=en
ter.
Regression
Page 7
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,fitness/dependent=fitness/method=enter.
00:00:00.00
00:00:00.01
4448 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 exerciseb . Enter
Dependent Variable: fitnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .390a .152 .150 16.9658122
Predictors: (Constant), exercisea.
Page 8
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
19156.131 1 19156.131 66.552 .000b
106788.189 371 287.839
125944.320 372
Dependent Variable: fitnessa.
Predictors: (Constant), exerciseb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
exercise
.000 .878 .000 1.000
.108 .013 .390 8.158 .000
Dependent Variable: fitnessa.
regression matrix=in(*)/variables=hardiness,stress/dependent=stress/method=ent
er.
Regression
Page 9
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,stress/dependent=stress/method=enter.
00:00:00.00
00:00:00.00
4448 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 hardinessb . Enter
Dependent Variable: stressa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .230a .053 .050 32.6457943
Predictors: (Constant), hardinessa.
Page 10
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
22084.533 1 22084.533 20.722 .000b
395392.467 371 1065.748
417477.000 372
Dependent Variable: stressa.
Predictors: (Constant), hardinessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
hardiness
.000 1.690 .000 1.000
-.203 .045 -.230 -4.552 .000
Dependent Variable: stressa.
comment estimates of direct effect of fitness on illness.
comment sufficient set is exercise.
regression matrix=in(*)/variables=fitness,illness,exercise/dependent=illness/m
ethod=enter.
Regression
Page 11
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,exercise/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 exercise, fitnessb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .292a .085 .080 59.9141072
Predictors: (Constant), exercise, fitnessa.
Page 12
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
124006.059 2 62003.030 17.272 .000b
1328189.090 370 3589.700
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), exercise, fitnessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
fitness
exercise
.000 3.102 .000 1.000
-1.036 .183 -.305 -5.653 .000
.037 .051 .039 .723 .470
Dependent Variable: illnessa.
comment sufficient set is hardiness. regression matrix=in(*)/variables=fitness,illness,hardiness/dependent=illness/
method=enter.
Regression
Page 13
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,hardiness/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 hardiness, fitnessb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .322a .104 .099 59.3110174
Predictors: (Constant), hardiness, fitnessa.
Page 14
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
150610.339 2 75305.169 21.407 .000b
1301584.810 370 3517.797
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), hardiness, fitnessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
fitness
hardiness
.000 3.071 .000 1.000
-.951 .168 -.280 -5.679 .000
-.231 .081 -.140 -2.845 .005
Dependent Variable: illnessa.
comment sufficient is stress. regression matrix=in(*)/variables=fitness,illness,stress/dependent=illness/met
hod=enter.
Regression
Page 15
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=fitness,illness,stress/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1stress, fitnessb
. Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .421a .177 .173 56.8324926
Predictors: (Constant), stress, fitnessa.
Page 16
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
257120.228 2 128560.114 39.803 .000b
1195074.921 370 3229.932
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), stress, fitnessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
fitness
stress
.000 2.943 .000 1.000
-.849 .162 -.250 -5.257 .000
.574 .089 .307 6.465 .000
Dependent Variable: illnessa.
comment estimates of direct effect of stress on illness.
comment sufficient set is exercise.
regression matrix=in(*)/variables=stress,illness,exercise/dependent=illness/me
thod=enter.
Regression
Page 17
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,exercise/dependent=illness/method=enter.
00:00:00.02
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 exercise, stressb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .346a .120 .115 58.7836892
Predictors: (Constant), exercise, stressa.
Page 18
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
173651.967 2 86825.984 25.127 .000b
1278543.182 370 3455.522
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), exercise, stressb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
stress
exercise
.000 3.044 .000 1.000
.628 .091 .337 6.897 .000
-.059 .046 -.063 -1.293 .197
Dependent Variable: illnessa.
comment sufficient set is hardiness. regression matrix=in(*)/variables=stress,illness,hardiness/dependent=illness/m
ethod=enter.
Regression
Page 19
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,hardiness/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 hardiness, stressb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .350a .123 .118 58.6805752
Predictors: (Constant), hardiness, stressa.
Page 20
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
178133.485 2 89066.742 25.866 .000b
1274061.664 370 3443.410
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), hardiness, stressb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
stress
hardiness
.000 3.038 .000 1.000
.597 .093 .320 6.398 .000
-.142 .082 -.086 -1.726 .085
Dependent Variable: illnessa.
comment sufficient set is fitness. regression matrix=in(*)/variables=stress,illness,fitness/dependent=illness/met
hod=enter.
Regression
Page 21
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=stress,illness,fitness/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1fitness, stressb
. Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .421a .177 .173 56.8324926
Predictors: (Constant), fitness, stressa.
Page 22
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
257120.228 2 128560.114 39.803 .000b
1195074.921 370 3229.932
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), fitness, stressb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
stress
fitness
.000 2.943 .000 1.000
.574 .089 .307 6.465 .000
-.849 .162 -.250 -5.257 .000
Dependent Variable: illnessa.
comment total effects of exercise on illness.
comment sufficient set is hardiness.
regression matrix=in(*)/variables=exercise,hardiness,illness/dependent=illness
/method=enter.
Regression
Page 23
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,hardiness,illness/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 hardiness, exerciseb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .181a .033 .028 61.6127126
Predictors: (Constant), hardiness, exercisea.
Page 24
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
47628.396 2 23814.198 6.273 .002b
1404566.753 370 3796.126
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), hardiness, exerciseb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
exercise
hardiness
.000 3.190 .000 1.000
-.080 .048 -.085 -1.659 .098
-.267 .084 -.163 -3.178 .002
Dependent Variable: illnessa.
comment sufficient set is stress. regression matrix=in(*)/variables=exercise,stress,illness/dependent=illness/me
thod=enter.
Regression
Page 25
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=exercise,stress,illness/dependent=illness/method=enter.
00:00:00.00
00:00:00.00
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 stress, exerciseb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .346a .120 .115 58.7836892
Predictors: (Constant), stress, exercisea.
Page 26
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
173651.967 2 86825.984 25.127 .000b
1278543.182 370 3455.522
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), stress, exerciseb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
exercise
stress
.000 3.044 .000 1.000
-.059 .046 -.063 -1.293 .197
.628 .091 .337 6.897 .000
Dependent Variable: illnessa.
comment total effects of hardiness on illness.
comment sufficient set is exercise.
regression matrix=in(*)/variables=hardiness,exercise,illness/dependent=illness
/method=enter.
Regression
Page 27
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,exercise,illness/dependent=illness/method=enter.
00:00:00.02
00:00:00.01
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 exercise, hardinessb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .181a .033 .028 61.6127126
Predictors: (Constant), exercise, hardinessa.
Page 28
ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
47628.396 2 23814.198 6.273 .002b
1404566.753 370 3796.126
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), exercise, hardinessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
hardiness
exercise
.000 3.190 .000 1.000
-.267 .084 -.163 -3.178 .002
-.080 .048 -.085 -1.659 .098
Dependent Variable: illnessa.
comment sufficient set is fitness. regression matrix=in(*)/variables=hardiness,fitness,illness/dependent=illness/
method=enter.
Regression
Page 29
Notes
Output Created
Comments
Input Filter
Weight
Split File
N of Rows in Working Data File
Matrix Input
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time
Elapsed Time
Memory Required
Additional Memory Required for Residual Plots
03-JAN-2015 21:07:12
<none>
<none>
<none>
8
working data file
User-defined missing values are treated as missing.Statistics are based on cases with no missing values for any variable used.regression matrix=in(*)/variables=hardiness,fitness,illness/dependent=illness/method=enter.
00:00:00.00
00:00:00.01
4672 bytes
0 bytes
Variables Entered/Removeda
ModelVariables Entered
Variables Removed Method
1 fitness, hardinessb . Enter
Dependent Variable: illnessa.
All requested variables entered.b.
Model Summary
Model R R SquareAdjusted R
SquareStd. Error of the
Estimate
1 .322a .104 .099 59.3110174
Predictors: (Constant), fitness, hardinessa.
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ANOVAa
ModelSum of Squares df Mean Square F Sig.
1 Regression
Residual
Total
150610.339 2 75305.169 21.407 .000b
1301584.810 370 3517.797
1452195.149 372
Dependent Variable: illnessa.
Predictors: (Constant), fitness, hardinessb.
Coefficientsa
Model
Unstandardized CoefficientsStandardized Coefficients
t Sig.B Std. Error Beta
1 (Constant)
hardiness
fitness
.000 3.071 .000 1.000
-.231 .081 -.140 -2.845 .005
-.951 .168 -.280 -5.679 .000
Dependent Variable: illnessa.
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