27. When the response is not normally distributed, we can replace the randomised block ANOVA with its
non-parametric counterpart; the Friedman test.
28. If we first arrange test units into similar groups before assigning treatments to them, the test design we
should use is the randomised block design.
29. If the data are not normally distributed, we can replace the independent-samples single-factor model of
the analysis of variance with its non-parametric counterpart, which is the Kruskal–Wallis test.
30. The sum of squares for treatments (SST) is the variation attributed to the differences between the
treatment means, while the sum of squares for error (SSE) measures the variation within the samples.
31. The calculated value of F in a one-way analysis is 7.88. The numbers of degrees of freedom for
numerator and denominator are 3 and 9, respectively. The most accurate statement to be made about
the p-value is that p-value < 0.01.
32. The number of degrees of freedom for the numerator or MST is 3 and that for the denominator or MSE
is 18. The total number of observations in the completely randomised design must equal 20.
33. A survey is to be conducted to compare the superannuation contributions made by employees from
three Victorian universities. Employees are to be randomly selected from each of the three universities
and the dollar amounts of their contributions recorded. The ANOVA model most likely to fit this
situation is the randomised block design.
34. Given the significance level 0.025, the F-value for the numbers of degrees of freedom d.f. = (4, 8) is
8.98.
35. One-way ANOVA is applied to three independent samples having means 12, 15 and 20, respectively.
If each observation in the third sample were increased by 40, the value of the F-statistic would
increase by 40.
36. The F-statistic in a one-way ANOVA represents the variation within the treatments divided by the
variation between the treatments.