Statistician, heal thyself: fighting statophobia at the source

Abstract

Notwithstanding the popularity of psychology courses throughout the world, educators face a constant and difficult problem of overcoming the fear of and dislike for statistics which represents one of the pillars of modern psychological science. Although the issue is complex and multifaceted, here I argue that “statophobia” might represent a rational and justified response to the sense of unease felt in contact with abstract statistical concepts which are often vague, circular or ill-defined. I illustrate the problem by briefly discussing two myths about the nature of probability and statistics, namely that probability and statistics generate knowledge and that the fault for not understanding probability lies solely with the subjective cognition which is incapable of comprehending deeper mathematical truth. I argue that the confident presentation of statistical methods hides numerous conceptual blind spots that students might be aware of and that need to be addressed before other causes of statistics anxiety can be tackled successfully.

Mathematics Anxiety and Statistics Anxiety. Shared but Also Unshared Components and Antagonistic Contributions to Performance in Statistics

“…Recent studies consider statistics anxiety as being conceptually different from mathematics anxiety (Cruise et al, 1985 ; Baloglu, 2003 ). Of course, statistics uses basic mathematical concepts and calculations but its learning contents differ from mathematics in various aspects (Aksentijevic, 2015 ). Statistic tasks in majors, such as education, psychology, or sociology are more closely related to verbal reasoning (Buck, 1987 ), they require probabilistic reasoning processes, such as making inferences or drawing conclusions from data (Baloglu, 1999 , 2003 ), and are often embedded into an applied context.…”

Building emotional rapport with students in statistics courses.

“…The subject itself has the potential to seem unapproachable; that is, many students hold beliefs that they either cannot successfully complete the course or that statistics knowledge may not be useful within their selected career fields (Onwuegbuzie, 2000). Thus, by debunking faulty beliefs about their statistics self-efficacy and the applicability of statistics within their future goals, instructors may battle their students’ “unrealistic expectations” about statistics and research design (Aksentijevic, 2015, p. 4). One reason that leads students to these unrealistic expectations is their difficulty with thinking in a statistical way.…”

“…One reason that leads students to these unrealistic expectations is their difficulty with thinking in a statistical way. Aksentijevic (2015) revealed that humans are genetically hard-wired to think in absolute terms (i.e., the effect of one variable on another will lead to an absolute result), but the philosophical underpinnings of statistics lead to more random results. That is, randomness (e.g., in probability reasoning) creates cognitive dissonance that is difficult for students to reconcile.…”