Module 20: Analysis of Variance (ANOVA)

Question 1

Omnibus null-hypothesis

Answer 1

This null-hypothesis states that there is no difference between any of the groups.

Question 2

Omnibus alternative hypothesis

Answer 2

states that at least one group mean differs from the others

Question 3

Bonferroni adjustment

Answer 3

in which the desired alpha level is divided by the number of tests or comparisons is typically used for this purpose.
• For example, if we are using the t test to make the three comparisons, we divide .05 by 3 and get .017. By not accepting the result as significant unless the alpha level is .017 or less, we minimize the chance of a Type I error when making multiple comparisons.

Con: increases chance of Type II error (failing to reject the null-hypothesis when it should have been rejected, namely, missing an effect of an independent variable)

Question 4

ANOVA (analysis of variance)

Answer 4

an inferential parametric statistical test for comparing the means of three or more groups. As its name indicates, this procedure allows us to analyze the variance in a study.

Question 5

Between participants designs one-way randomized ANOVA

Answer 5

“randomized” indicates that the participants are randomly assigned to conditions in a between-participants design (different groups). “One way” indicates that there is only one independent variable.

Question 6

Grand mean

Answer 6

the mean performance across all participants in all conditions

Question 7

Error variance

Answer 7

the amount of variability among the scores caused by chance or uncontrolled variables such as individual differences between participants.

Question 8

Within-group variance

Answer 8

the variance within each condition or group

Question 9

Between-groups variance

Answer 9

is an estimate of systematic variance and error variance.

Question 10

Systematic variance

Answer 10

the effect of the independent variable and any confounds

Question 11

Conceptual formula of F-ratio

Answer 11

F-ratio = Between-groups variance / within-groups variance

Or

F-ratio = (systematic variance + error variance) / error variance

Question 12

Within-groups sum of squares

Answer 12

The sum of the squared deviations of each score from its group mean.

Question 13

Between-groups sum of squares

Answer 13

The sum of the squared deviations of each group’s mean from the grand mean, multiplied by the number of participants in each group.

Question 14

Mean square

Answer 14

An estimate of either variance between groups or variance within groups.

Question 15

Eta-squared N2

Answer 15

An inferential statistic for measuring effect size with an ANOVA. Rules-of-thumb for effect size of the eta-squared:

• .01 = small
• .06 = medium
• .14 = large

Question 16

Tukey’s Post Hoc Test

Answer 16

When used with an ANOVA, a means of comparing all possible pairs of groups to determine which ones differ significantly from each other. This test is done after the actual research.

Question 17

Tukey’s honestly significant difference (HSD)

Answer 17

which allows a researcher to make all pairwise comparisons among the sample means in a study while maintaining an acceptable alpha