Analysis of variance (ANOVA) (p. 276) F statistic (p. 276) Between-groups variance (p. 276) Within-groups variance (p. 276) one-way ANOVA (p. 277) between-groups ANOVA (p. 277) within-groups ANOVA (p. 277) Homoscedastic (p. 278) Heteroscedastic (p. 278) source table (p. 285) grand mean (p. 287) R2 (p. 294) post hoc test (p. 294) Tukey HSD test (p. 294) | Between-groups variance is an estimate of the population variance, based on the differences among the means. A between-groups ANOVA is a hypothesis test in which there are more than two samples, and each sample is composed of different participants. R2 is the proportion of variance in the dependent variable that is accounted for by the independent variable. A post hoc test is a statistical procedure frequently carried out after the null hypothesis has been rejected in an analysis of variance; it allows us to make multiple comparisons among several means; often referred to as a follow-up test. The Tukey HSD test is a widely used post hoc test that determines the differences between means in terms of standard error; the HSD is compared to a critical value; sometimes called the q test. Homoscedastic populations are those that have the same variance; homoscedasticity is also called homogeneity of variance. Analysis of variance (ANOVA) is a hypothesis test typically used with one or more nominal (and sometimes ordinal) independent variables (with at least three groups overall) and a scale dependent variable. Within-groups variance is an estimate of the population variance, based on the differences within each of the three (or more) sample distributions. The F statistic is a ratio of two measures of variance: (1) between-groups variance, which indicates differences among sample means, and (2) within-groups variance, which is essentially an average of the sample variances. Heteroscedastic populations are those that have different variances. The grand mean is the mean of every score in a study, regardless of which sample the score came from. A source table presents the important calculations and final results of an ANOVA in a consistent and easy-to-read format. A within-groups ANOVA is a hypothesis test in which there are more than two samples, and each sample is composed of the same participants; also called a repeated-measures ANOVA. A one-way ANOVA is a hypothesis test that includes both one nominal independent variable with more than two levels and a scale dependent variable. |