Analysis of Variance (ANOVA) results in the calculation of the F Statistic and interpretation of this statistic will inform you as to...?
A. Which mean significantly differs from others
B. Whether one or more of the means is significantly defferent from one or more of the others in the study
C. How the variables are associated with each other
D. How many means differ significantly from the "Grand Mean"
B. Whether one or more of the means is significantly different from one or more of the others in the study
The correct answer is B. Whether one or more of the means is significantly different from one or more of the others in the study.
In order to interpret the F-statistic in ANOVA, you first need to understand the basics of ANOVA analysis. ANOVA is a statistical test that is used to compare the means of multiple groups and determine if there are any significant differences.
To calculate the F-statistic, you first calculate the between-group variance and the within-group variance. The between-group variance represents the variability between the means of the different groups, while the within-group variance represents the variability within each group.
The F-statistic is calculated by dividing the between-group variance by the within-group variance. A high F-value indicates a larger difference between the means of the groups compared to the variation within each group, which suggests that there is a significant difference between at least one pair of means. On the other hand, a low F-value indicates that the variation within each group is similar to the differences between the means, suggesting that there is no significant difference between the groups.
Therefore, by interpreting the F-statistic, you can determine whether one or more of the means is significantly different from one or more of the others in the study.