The purpose of this article is to present a critical analysis of current research practices in the study of behavior from the point of view of scientific realism. Although the so-called “replication crisis” observed in the psychological and health sciences has led to various proposals for improving research quality, most of those proposals take the standard linear input–output approach for granted, where behavioral variability is seen as the result of uncontrolled random variables hiding the true input–output relations. Aggregate data and the computation of sample statistics are used to estimate population parameters, the true reality behind appearances. In this paper, I offer a different interpretation: variability is a fact of behavior necessary for successful performance, not the result of some unknown variables randomly affecting individual outputs. Research models that take individual behavior with all of its complexity as the real thing, can help us overcome the limitations of the standard approach to research. As an illustration, I also describe two approaches to behavioral investigations that do not rely on standard statistical analysis for producing genuine knowledge: perceptual control theory and observation-oriented modeling.