Most behavior analysts would agree that best-practice behavior-analytic services require, at a minimum, problem identification, establishing operational definitions, establishing assessment and treatments goals, achieving accurate data collection, and evaluating treatment in a reasonably conservative experimental design. Most behavior analysts would also agree that taking those steps in the context of problem solving should occur in a single-subject design. That is, behavior analysts are likely to focus on behavior change at the level of the individual response class rather than measures of central tendency within a large group of individuals (Johnston & Pennypacker, 1980). Interestingly, this methodology (i.e., single-subject design and the focus in the individual) is relatively rare in psychological research (Friman, 2010). Establishing functional relations typically relies on determining the likelihood that one may draw an inference about the relationship between an independent variable and dependent variable at some arbitrarily agreed upon acceptable level of error (e.g., p = .05). This is in stark contrast to behavior analytic research and practice, in which statistics are relatively rare. The criterion for drawing an inference about the relationship between an independent variable and dependent variable is usually the judgment of a "visual inspector", who must decide if a reasonable demonstration of experimental control and change of social significance are evident when the data are depicted in graphical form (Baer, Wolf, & Risley, 1968). The advantages and disadvantages of these disparate approaches have been described, discussed, and argued elsewhere (e.g., Baer, 1977; Johnston & Pennypacker, 1980; Michael, 1974). The field of ABA, though, has almost categorically adopted single-subject methodology and logic as the core of its practice and research.