Single‐Variable Between‐Subjects Research

This chapter focuses on research that involves more than two levels or conditions of a single independent variable. It examines an extremely useful statistical technique known as the analysis of variance (ANOVA). By using several examples from the published research literature, the chapter illustrates the value of the ANOVA approach to design and analysis. Researchers use the general linear model to describe how the ANOVA analyzes the data. Specifically, the ANOVA allows one to examine the within-groups and between-groups variance. The within-groups variance represents the effects of random events that influence the difference among the scores in the individual groups. The between-groups variance represents the differences among the group means. These variance estimates are used to determine the F-ratio. Similarly, the post hoc tests, such as Tukey’s honestly significant difference (HSD), is used to determine which pairs of means are different from each other. Controlled Vocabulary Terms analysis of variance; causality; dependent variables; independent variables; sampling distribution