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# Statistics - Research Paper Example

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Your Name Due Date Course Statistics Report II This study analyzed the number of phone calls made home by a small sample (n=40) of undergraduate students. In this study, the number of phone calls made home was the dependent variable, and both the year of the student (freshmen, sophomore, junior, or senior) and the gender of the student were independent variables…

## Extract of sample "Statistics"

Due Statistics Report II This study analyzed the number of phone calls made home by a small sample (n=40) of undergraduate students. In this study, the number of phone calls made home was the dependent variable, and both the year of the student (freshmen, sophomore, junior, or senior) and the gender of the student were independent variables. Because this study has two independent variables and one dependent variable, a factorial ANOVA design is most appropriate. The gender factor has two levels: male and female, and the year factor has four levels (freshmen, sophomore, junior, or senior), meaning we have a 4x2 ANOVA design. Because we have a 4x2 ANOVA design, one interaction effect is possible (between the gender and year factors) and two main effects are possible. A univariate analysis of variance (factorial ANOVA) was conducted on SPSS 18.0 to determine the significance of these three possible effects. The first thing to check when conducting a factorial ANOVA is Levene’s Test of the equal variance assumption. This test had a p=0.624, indicating that the equal variance assumption has not been violated. Since we can assume equal variance, we can use the given F and p statistics given in the between subjects table. The 4x2 ANOVA failed to demonstrate an interaction effect at the 0.05 error level between class and gender (F(3,32)=0.901, p=0.451), but did demonstrate a significant main effect for class (F(3,32)=18.342, p Read More
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