This chapter is concerned with experimental and quasi-experimental designs and the statistical approaches most commonly employed in conjunction with them. The section on design describes basic configurations of true experiments and quasi-experiments, explains the advantages and disadvantages of each of these two families of design, and discusses some general considerations for either type of design. The section on analysis focuses on the analysis of experimental and quasi-experimental data with continuous response variables (chapter 9, this volume, for information about the analysis of qualitative dependent variables). This section begins with a brief discussion of preliminary, descriptive analyses, followed by a description of methods for inferential analyses. Because experimental and quasi-experimental studies are designed to address questions about group differences in average performance, data from these studies are typically analyzed using some form of an analysis of variance (ANOVA) or extensions of that technique. However, it is important to note that the statistical techniques discussed here may be appropriate for the analysis of nonexperimental data; indeed, these procedures are appropriate for the analysis of data from any investigation in which the primary research questions involve an assessment of differences in group performance.
True experiments involve the manipulation of one or more independent variables by the investigator and random assignment of subjects to experimental groups or treatments.