Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
Tests of Between-SubjectsEffects
|
DependentVariable: Post-test
|
DependentVariable:
Post-test
|
DependentVariable: Post-test
|
DependentVariable: Post-test
|
DependentVariable:
Post-test
|
DependentVariable: Post-test
|
DependentVariable: Post-test
|
Source
|
Source
|
Type III Sum of Squares
|
df
|
MeanSquare
|
F
|
Sig.
|
Intercept
|
Hypothesis
|
260556,196
|
1
|
260556,196
|
184,459
|
,000
|
|
Error
|
9576,958
|
6,780
|
1412,539a
|
|
|
Groups
|
Hypothesis
|
2259,296
|
1
|
2259,296
|
14,409
|
,001
|
|
Error
|
4013,284
|
25,596
|
156,792b
|
|
|
Pre-test
|
Hypothesis
|
15786,726
|
6
|
2631,121
|
18,227
|
,001
|
|
Error
|
866,106
|
6
|
144,351c
|
|
|
Groups * Pretest
|
Hypothesis
|
866,106
|
6
|
144,351
|
,852
|
,533
|
|
Error
|
15931,456
|
94
|
169,484d
|
|
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
a. ,505 MS(pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
b. ,505 MS(groups * pre-test) + ,495 MS(Error)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
c. MS(Groups * pre-test)
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|
d. MS(Error)
The table above shows that we meet the assumptions of homogeneity
between regression curves. Therefore, ANCOVA analysis can be performed
in this study.
Findings
In this section, the analysis of the hypothesis of the research and the
results of these analyzes are given.
|