In: Statistics and Probability
A university wants to determine if students from different
majors are equally likely to be cited...
A university wants to determine if students from different
majors are equally likely to be cited for academic dishonesty. They
average instances of documented cheating across 10 years for three
different academic majors and find the following results: Business
Administration (M = 5.1; N = 10), Fine Art
(M = 1.9; N = 10), and Nursing (M = 3.2;
N = 10). They also calculated the between-group and
within-group sum of squares (SSB = 301.6; SSW
=1343.8). Use a one-way ANOVA (where α = .01) to determine if there
are significant differences in cheating rates by major.
- Identify the alternative hypothesis (F tests
are always nondirectional)
- List your degrees of freedom (within)
- List your degrees of freedom (between)
- List your mean squares between groups
- List your mean squares within groups
- List your F test statistic
- List your critical F value(s)
- Are there statistically significant differences in
cheating between majors? (Yes/No)
- Calculate partial eta-squared (η2) for the
effect of major on cheating rates (list as decimal,
0.xx)
- Calculate Tukey’s HSD
- Use Tukey’s HSD to determine if the difference in
cheating rates between Business Administration majors and Fine
Art majors is statistically significant
(Yes/No)