Reporting a Factorial ANOVA

Reporting the Study using APA

Reporting the Study using APA• You can report that you conducted a Factorial

ANOVA by using the template below.

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).”

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:

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.”

Reporting Results using APA

Reporting Results using APA• You can report data from your own experiments by

using the example below.

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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