Reporting a Factorial ANOVA
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A two-way ANOVA was conducted to examine the effects of athlete type (football, basketball, soccer) and age (younger, older) on slices of pizza eaten. There were significant main effects of athlete type and an interaction between athlete type and age, but no main effect of age. Football players ate the most pizza, followed by basketball players and then soccer players.
![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).”](https://image.slidesharecdn.com/reportingafactorialanova-140917111749-phpapp01/85/Reporting-a-Factorial-ANOVA-4-320.jpg)
![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:](https://image.slidesharecdn.com/reportingafactorialanova-140917111749-phpapp01/85/Reporting-a-Factorial-ANOVA-5-320.jpg)
![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.”](https://image.slidesharecdn.com/reportingafactorialanova-140917111749-phpapp01/85/Reporting-a-Factorial-ANOVA-6-320.jpg)
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