ABSTRACT
This chapter explains general design classifications: between-groups, within-subjects, and mixed designs, which are especially important for determining the proper statistical approach to be used in data analysis. It presents the diagrams, classifications, and descriptions, which are for difference questions, using the randomized experimental, quasi-experimental, and comparative approaches to research. Appropriate classification and description of the design are crucial for choosing the appropriate inferential statistic. Between-groups designs are defined as designs where each participant in the research is in one and only one condition or group. In within-subjects designs, each participant in the research receives or experiences all of the conditions of the independent variable to complete the study. A mixed design has at least one between-groups independent variable and at least one within-subjects independent variable; thus, it has a minimum of two independent variables. In either a between-groups design or a within-subjects design, if the design has only one independent variable it should be described as a single-factor design.
