Reporting a Factorial ANOVA

1. Reporting a Factorial ANOVA

2. Reporting the Study using APA

3. Reporting the Study using APA
• You can report that you conducted a Factorial
ANOVA by using the template below.

4. Reporting the Study using APA
• You can report that you conducted a Factorial
ANOVA by using the template below.
• “A Factorial ANOVA was conducted to compare the
main effects of [name the main effects (IVs)] and
the interaction effect between (name the
interaction effect) on (dependent variable).”

5. Reporting the Study using APA
• You can report that you conducted a Factorial
ANOVA by using the template below.
• “A Factorial ANOVA was conducted to compare the
main effects of [name the main effects (IVs)] and
the interaction effect between (name the
interaction effect) on (dependent variable).”
• Here is an example:

6. Reporting the Study using APA
• You can report that you conducted a Factorial
ANOVA by using the template below.
• “A Factorial ANOVA was conducted to compare the
main effects of [name the main effects (IVs)] and
the interaction effect between (name the
interaction effect) on (dependent variable).”
• Here is an example:
• “A Factorial ANOVA was conducted to compare
the main effects of type of athlete and age and the
interaction effect between type of athlete and age
on the number of slices of Pizza eaten in one
sitting.”

7. Reporting Results using APA

8. Reporting Results using APA
• You can report data from your own experiments by
using the example below.

9. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.

10. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.

11. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.

12. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.

13. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34). The interaction effect was significant, F(2, 63) =
13.36, p < .001.

14. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34). The interaction effect was significant, F(2, 63) =
13.36, p < .001.

15. Reporting Results using APA
• You can report data from your own experiments by
using the example below.
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
• Note: A posthoc would provide information about
which levels within each independent variable
were significant.

16. Reporting Results using APA
• Just fill in the blanks by using the SPSS output

17. Reporting Results using APA
• Just fill in the blanks by using the SPSS output
• Let’s break down these results using the output:

18. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.

19. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

20. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

21. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

22. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

23. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

24. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD =
1.99), basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD =
1.53. The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05,
indicating that the effect for age was not significant, younger (M = 5.97, SD =
3.97) and older (M = 5.39, SD = 2.34) The interaction effect was significant,
F(2, 63) = 13.36, p < .001. Descriptive Statistics
Dependent Variable: Pizza_Slices
Athletes Age Mean Std. Deviation N
Football Older 8.0000 .77460 11
Younger 10.6667 1.92275 12
Total 9.3913 1.99406 23
Basketball Older 4.8182 1.16775 11
Younger 5.5000 1.56670 12
Total 5.1739 1.40299 23
Soccer Older 3.3636 1.80404 11
Younger 1.7500 .62158 12
Total 2.5217 1.53355 23
Total Older 5.3939 2.34440 33
Younger 5.9722 3.97482 36
Total 5.6957 3.28680 69

25. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001. Descriptive Statistics
Dependent Variable: Pizza_Slices
Athletes Age Mean Std. Deviation N
Football Older 8.0000 .77460 11
Younger 10.6667 1.92275 12
Total 9.3913 1.99406 23
Basketball Older 4.8182 1.16775 11
Younger 5.5000 1.56670 12
Total 5.1739 1.40299 23
Soccer Older 3.3636 1.80404 11
Younger 1.7500 .62158 12
Total 2.5217 1.53355 23
Total Older 5.3939 2.34440 33
Younger 5.9722 3.97482 36
Total 5.6957 3.28680 69

26. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001. Descriptive Statistics
Dependent Variable: Pizza_Slices
Athletes Age Mean Std. Deviation N
Football Older 8.0000 .77460 11
Younger 10.6667 1.92275 12
Total 9.3913 1.99406 23
Basketball Older 4.8182 1.16775 11
Younger 5.5000 1.56670 12
Total 5.1739 1.40299 23
Soccer Older 3.3636 1.80404 11
Younger 1.7500 .62158 12
Total 2.5217 1.53355 23
Total Older 5.3939 2.34440 33
Younger 5.9722 3.97482 36
Total 5.6957 3.28680 69

27. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

28. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

29. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001. Descriptive Statistics
Dependent Variable: Pizza_Slices
Athletes Age Mean Std. Deviation N
Football Older 8.0000 .77460 11
Younger 10.6667 1.92275 12
Total 9.3913 1.99406 23
Basketball Older 4.8182 1.16775 11
Younger 5.5000 1.56670 12
Total 5.1739 1.40299 23
Soccer Older 3.3636 1.80404 11
Younger 1.7500 .62158 12
Total 2.5217 1.53355 23
Total Older 5.3939 2.34440 33
Younger 5.9722 3.97482 36
Total 5.6957 3.28680 69

30. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001. Descriptive Statistics
Dependent Variable: Pizza_Slices
Athletes Age Mean Std. Deviation N
Football Older 8.0000 .77460 11
Younger 10.6667 1.92275 12
Total 9.3913 1.99406 23
Basketball Older 4.8182 1.16775 11
Younger 5.5000 1.56670 12
Total 5.1739 1.40299 23
Soccer Older 3.3636 1.80404 11
Younger 1.7500 .62158 12
Total 2.5217 1.53355 23
Total Older 5.3939 2.34440 33
Younger 5.9722 3.97482 36
Total 5.6957 3.28680 69

31. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68

32. Reporting Results using APA
• A two-way analysis of variance was conducted on the influence of two
independent variables (athlete type, age) on the number of slices of pizza eaten
in one sitting. Athlete type included three levels (football, basketball, soccer
players) and age consisted of two levels (younger, older). All effects were
statistically significant at the .05 significance level except for the Age factor. The
main effect for athlete type yielded an F ratio of F(2, 63) = 136.2, p < .001,
indicating a significant difference between football players (M = 9.39, SD = 1.99),
basketball players (M = 5.17, SD = 1.40) and soccer players (M = 2.52, SD = 1.53.
The main effect for age yielded an F ratio of F(1, 63) = 2.9, p > .05, indicating
that the effect for age was not significant, younger (M = 5.97, SD = 3.97) and
older (M = 5.39, SD = 2.34) The interaction effect was significant, F(2, 63) =
13.36, p < .001.
Tests of Between-Subjects Effects
Dependent Variable: Pizza_Slices
Source
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model 610.510a 5 122.102 61.986 .000
Intercept 2224.308 1 2224.308 1129.195 .000
Athletes 536.550 2 268.275 136.193 .000
Age 5.758 1 5.758 2.923 .092
Athletes * Age 52.666 2 26.333 13.368 .000
Error 124.098 63 1.970
Total 2973.000 69
Corrected Total 734.609 68