Randomization of large number of participants to different treatment groups is often not a feasible or preferable way to answer questions of immediate interest to professional practice. Single case designs (SCDs) are a class of research designs that are experimental in nature but require only a few participants, all of whom receive the treatment(s) of interest. SCDs are particularly relevant when a dependent variable of interest can be measured repeatedly over time across two conditions (e.g., baseline and intervention). Rather than using randomization of large numbers of participants, SCD researchers use careful and prescribed ordering of experimental conditions, which allow researchers to improve internal validity by ruling out alternative explanations for behavior change. This article describes SCD logic, control of threats to internal validity, the use of randomization and counterbalancing, and data analysis in the context of single case research.