Stanislaw Ulam famously said “Using a term like nonlinear science is like referring to the bulk of zoology as the study of non-elephant animals.” The notion that we live in a complexity driven world is non-controversial. The controversy comes in how we operationalize it. With this in mind, I will reflect on what we can learn from the vast body of non-systems research in fields like psychology. This will entail an attempt at linking classically taught statistics to our systems equivalents along with the impacts of various methods from cross-sectional and ecological momentary assessments to the role of measurement. In the end, this will be a pitch to not throw out the baby with the bathwater, but instead to tactically draw upon the past to help us inform for a more complete sense of our phenomena.

Bio: Jonathan Butner received his Ph.D. in Psychology in 2002 from Arizona State University and is currently a professor in the Department of Psychology at the University of Utah. He was trained as both a social and quantitative psychologist, but now self-describes as a dynamical systems theorist or complexity theorist. His research profile entails a combination of applied systems modeling and development of statistical methodologies within the confines of social science that address multivariate multilevel nonlinear data structures.