As data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however,…

We present a unique and innovative course, Biostatistical Literacy, developed at the University of Minnesota. The course is aimed at public health graduate students and health sciences professionals. Its goal is to develop students' ability to read and interpret statistical results in the medical and public health literature. The content spans the…

Statistics anxiety is a reality among many students that may affect their academic and professional lives. Although there are instructional strategies proven to demonstrate advanced statistical concepts, a method to mitigate statistics anxiety in introductory courses is lacking. This research examines the effectiveness of three interventions used…

Undergraduate students outside Statistics major frequently take only one class of Basic Statistics or Introductory Statistics during their studies. As a consequence, many of them have little knowledge about advanced statistical methods, such as logistic regression, nonparametric procedures, and multivariate analysis, although they might need to…

This article demonstrates how data from a biology paper, which analyzes the relationship between mass and metabolic rate for two species of marine bryozoan, can be used to teach a variety of regression topics to both introductory and advanced students. A thorough analysis requires intelligent data wrangling, variable transformations, and…

Statistical association is a key facet of statistical literacy: claims based on relationships between variables or ideas rooted in data are found everywhere in media and discourse. A key development in introductory statistics curricula is the use of simulation-based inference, which has shown positive outcomes for students, especially in regards…

A persistent problem in teaching introductory statistics has been helping students overcome their fears and the abstract nature of what they need to learn. Students' own contextualised stories are argued to present an opportunity for humanising the abstract, helping reduce student fears to complement traditional teaching approaches. This paper…

In an increasingly data-driven world, statistical literacy is a necessity yet statistical learning is often inhibited by statistics anxiety. Using the Auzmendi Scale to Measure Attitude toward Statistics (ASMAS), this study examines how statistics anxiety in university students is related to other dimensions of their attitudes toward statistics…

This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…

Background: Student anxiety about statistics may lead to poorer learning outcomes. Objective: The purpose of this study was to evaluate an exercise designed to teach students in an introductory statistics class the principles of bivariate regression and to emphasize how statistical tools used by psychologists are also implemented in other fields.…

We present an instructional approach to teaching causal inference using Bayesian networks and "do"-Calculus, which requires less prerequisite knowledge of statistics than existing approaches and can be consistently implemented in beginner to advanced levels courses. Moreover, this approach aims to address the central question in causal…

Though statistical testing is commonly practiced, the logic of statistical tests is confusing, thinking about distributions is difficult, and the way statisticians formulate expectations as probability distributions is poorly understood. To support instruction, the statistics education community has increasingly utilized simulation-based…

Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…

Metaphors are well-known tools for teaching statistics to novices. However, educators might overlook metaphor theoretical developments that offer nuanced and testable perspectives on their pedagogical applications. This article introduces the notion of metaphor types--"correspondence" (CO) and "class inclusion" (CI)--as…

Introduction: Student motivation is a critical predictor of academic achievement, engagement, and success in higher education. Motivating students is a crucial aspect of effective teaching. Statement of the Problem: Although there is a wealth of research on student motivation, practical guidance for putting theory into practice in challenging…