Lecture 15: Analysis of Variance (ANOVA)

These flashcards cover essential vocabulary related to ANOVA, including key concepts, definitions, and statistical methods relevant to the lecture.

ANOVA (Analysis of Variance)

A statistical method used to determine if there are significant differences between the means of three or more independent groups.

Null Hypothesis (H0) in ANOVA

The hypothesis that states there is no difference among the group means; stated as H0: µ1 = µ2 = µ3 = … = µk.

Alternative Hypothesis (HA) in ANOVA

The hypothesis that states at least one group mean is different from the others.

Mean Squares (MS)

A measure used in ANOVA to determine variance; calculated as the sum of squares divided by the corresponding degrees of freedom.

F-Ratio

The ratio of the variance between the group means to the variance within the groups; used in ANOVA to test the significance of the means.

Tukey-Kramer Test

A post-hoc test used after ANOVA to find means that are significantly different from each other while controlling for Type I error.

Fixed Effects

ANOVA model where the categories of the explanatory variable are predetermined and conclusions apply only to fixed groups.

Random Effects

ANOVA model where the categories of the explanatory variable are randomly chosen from a larger population.

Kruskal-Wallis Test

A non-parametric test used to compare three or more independent groups; an alternative to one-way ANOVA when the assumptions of ANOVA are not met.

Robustness of ANOVA

The ability of ANOVA to produce reliable results even when its assumptions are somewhat violated, especially with large sample sizes.