Data science is inherently collaborative as individuals across fields and sectors use quantitative data to answer relevant questions. As a result, there is a growing body of research regarding how to teach interdisciplinary collaboration skills. However, much of the work evaluating methods of teaching statistics and data science collaboration…

R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…

The proficient handling of data can undoubtedly be regarded as a key skill for the future. However, the need for data competencies is not limited to traditional professions in the information technology environment but is rather necessary across industries and work fields. Consequently, there is a call to integrate such Data Literacy and Data…

Self-efficacy is associated with a range of educational outcomes, including science and math degree attainment. Project-based statistics courses have the potential to increase students' math self-efficacy because projects may represent a mastery experience, but students enter courses with preexisting math self-efficacy. This study explored…

Understanding statistics is essential for engineers. However, statistics courses remain challenging for many students, as they find them rigid, abstract, and demanding. Prior research has indicated that using project-based learning (PjBL) to demonstrate the relevance of statistics to students can have a significant effect on learning in these…

Our study compared the performance of students enrolled in a graduate-level introductory biostatistics course in an online versus a traditional in-person learning environment at a school of public health in the United States. We extracted data for students enrolled in the course online and in person from 2013 to 2018. We compared average quiz and…

Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

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…