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ANOVA and MANOVA in SPSS

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I have a student version of SPSS: The following was the question. I am unable to do a multivariate so I performed a univariate.

9.
a. Conduct a multivariate ANOVA (Analyze, General Linear Model, multivariate, dep vars are the 5 quizzes and the fixed factor (IV) is "final".
In your own words, what is the interpretation of the multivariate test F-ratio obtained?

Since a multivariate cannot be performed with the student version of SPSS. "Quiz " was used individually as the DV & "final" was used as the fixed IV.

Between-Subjects Factors

N
final 40 1
42 1
43 1
48 2
49 3
50 3
52 4
53 5
54 2
55 3
56 1
57 6
58 2
59 4
60 7
61 5
62 7
63 7
64 3
65 3
66 4
67 3
68 8
69 2
70 2
71 4
72 3
73 2
74 4
75 3

Tests of Between-Subjects Effects

Dependent Variable: quiz1
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 343.715(a) 29 11.852 2.999 .000
Intercept 3448.294 1 3448.294 872.491 .000
final 343.715 29 11.852 2.999 .000
Error 296.418 75 3.952
Total 6494.000 105
Corrected Total 640.133 104
a R Squared = .537 (Adjusted R Squared = .358)

Tests of Between-Subjects Effects

Dependent Variable: quiz2
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 132.596(a) 29 4.572 2.426 .001
Intercept 4429.599 1 4429.599 2350.078 .000
final 132.596 29 4.572 2.426 .001
Error 141.365 75 1.885
Total 6962.000 105
Corrected Total 273.962 104
a R Squared = .484 (Adjusted R Squared = .284)

Tests of Between-Subjects Effects

Dependent Variable: quiz3
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 295.011(a) 29 10.173 2.946 .000
Intercept 4087.604 1 4087.604 1183.892 .000
final 295.011 29 10.173 2.946 .000
Error 258.951 75 3.453
Total 7242.000 105
Corrected Total 553.962 104
a R Squared = .533 (Adjusted R Squared = .352)

Tests of Between-Subjects Effects

Dependent Variable: quiz4
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 253.242(a) 29 8.732 2.278 .002
Intercept 3952.461 1 3952.461 1030.868 .000
final 253.242 29 8.732 2.278 .002
Error 287.558 75 3.834
Total 6929.000 105
Corrected Total 540.800 104
a R Squared = .468 (Adjusted R Squared = .263)

Tests of Between-Subjects Effects

Dependent Variable: quiz5
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 139.354(a) 29 4.805 1.950 .011
Intercept 4363.346 1 4363.346 1771.032 .000
final 139.354 29 4.805 1.950 .011
Error 184.780 75 2.464
Total 6822.000 105
Corrected Total 324.133 104
a R Squared = .430 (Adjusted R Squared = .209)

All the sig values are < .05, therefore the Null hypothesis are rejected. Quiz 1 had the highest F value (2.999). Quiz 5 had the lowest (1.950). But w

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I have a student version of SPSS: The following was the question. I am unable to do a multivariate so I performed a univariate.

9.
a. Conduct a multivariate ANOVA (Analyze, General Linear Model, multivariate, dep vars are the 5 quizzes and the fixed factor (IV) is "final".
In your own words, what is the interpretation of the multivariate test F-ratio obtained?

Since a multivariate cannot be performed with the student version of SPSS. "Quiz " was used individually as the DV & "final" was used as the fixed IV.

Between-Subjects Factors

N
final 40 1
42 1
43 1
48 2
49 3
50 3
52 4
53 5
54 2
55 3
56 1
57 6
58 2
59 4
60 7
61 5
62 7
63 7
64 3
65 3
66 4
67 3
68 8
69 2
70 2
71 4
72 3
73 2
74 4
75 3

Tests of Between-Subjects Effects

Dependent Variable: quiz1
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 343.715(a) 29 11.852 2.999 .000
Intercept 3448.294 1 3448.294 872.491 .000
final 343.715 29 11.852 2.999 .000
Error 296.418 75 3.952
Total 6494.000 105
Corrected Total 640.133 104
a R Squared = .537 (Adjusted R Squared = .358)

Here the null hypothesis tested

H0: There is no significant difference in average score of Quiz1 among the 30 levels of Final.

Conclusion : We reject the null Hypothesis since sig value is less than 0.05

R Squared = .537 (Adjusted R Squared = .358) means that 35.8 % variability in quiz 1 can be explained by the variable Final. Adjusted R Square is calculated from R Square value by adding a correction factor for sample size

Tests of Between-Subjects Effects

Dependent Variable: quiz2
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 132.596(a) 29 4.572 2.426 .001
Intercept 4429.599 1 4429.599 2350.078 .000
final 132.596 29 4.572 2.426 .001
Error 141.365 75 1.885
Total 6962.000 105
Corrected Total 273.962 104
a R Squared = .484 (Adjusted R Squared = .284)

Here the null hypothesis tested

H0: There is no significant difference in average score of Quiz 2 among the 30 levels of Final.

Conclusion : We reject the null Hypothesis since sig value is less than 0.05

R Squared =0 .484 (Adjusted R Squared = .284)
means that 28.4 % variability in quiz 2 can be explained by the variable Final.]

Tests of Between-Subjects Effects

Dependent Variable: quiz3
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 295.011(a) 29 10.173 2.946 .000
Intercept 4087.604 1 4087.604 1183.892 .000
final 295.011 29 10.173 2.946 .000
Error 258.951 75 3.453
Total 7242.000 105
Corrected Total 553.962 104
a R Squared = .533 (Adjusted R Squared = .352)

Here the null hypothesis tested

H0: There is no significant difference in average score of Quiz 3 among the 30 levels of Final.

Conclusion : We reject the null Hypothesis since sig value is less than 0.05

R Squared = .533 (Adjusted R Squared = .352)

means that 35.2 % variability in quiz 3 can be explained by the variable Final.]

Tests of Between-Subjects Effects

Dependent Variable: quiz4
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 253.242(a) 29 8.732 2.278 .002
Intercept 3952.461 1 3952.461 1030.868 .000
final 253.242 29 8.732 2.278 .002
Error 287.558 75 3.834
Total 6929.000 105
Corrected Total 540.800 104
a R Squared = .468 (Adjusted R Squared = .263)

Here the null hypothesis tested

H0: There is no significant difference in average score of Quiz 4 among the 30 levels of Final.

Conclusion : We reject the null Hypothesis since sig value is less than 0.05
R Squared = .468 (Adjusted R Squared = .263)
means that 26.3 % variability in quiz 4 can be explained by the variable Final.]

Tests of Between-Subjects Effects

Dependent Variable: quiz5
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 139.354(a) 29 4.805 1.950 .011
Intercept 4363.346 1 4363.346 1771.032 .000
final 139.354 29 4.805 1.950 .011
Error 184.780 75 2.464
Total 6822.000 105
Corrected Total 324.133 104
a R Squared = .430 (Adjusted R Squared = .209)
Here the null hypothesis tested

H0: There is no significant difference in average score of Quiz 5 among the 30 levels of Final.

Conclusion : We reject the null Hypothesis since sig value is less than 0.05
R Squared = .430 (Adjusted R Squared = .209) means that 20.9% variability in quiz 5 can be explained by the variable Final.]

All the sig values are < .05, therefore the Null hypothesis are rejected. Quiz 1 had the highest F value (2.999). Quiz 5 had the lowest (1.950). But what am I really looking at? What else can I interpret?

Hypothesis F value
1 2.999
2 2.426
3 2.946
4 2.276
5 1.950
High value of F indicates that there is more difference among the 30 levels of Final .
Thus here we claim that there high degree of dissimilarity for mean value of Quiz 1 among 30 level of Final and this type of difference is comparatively low for the varia

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