There is wide agreement that ethical considerations are a valuable aspect of a data science curriculum, and to that end, many data science programs offer courses in data science ethics. There are not always, however, explicit connections between data science ethics and the centuries-old work on ethics within the discipline of philosophy. Here, we…

Data literacy for students in nonquantitative fields is important as statistics become the grammar of research and how the world's decisions are made. Statistics courses are typically offered by mathematics or statistics departments or by social and natural sciences such as economics, political science, psychology, and biology. Here we discuss how…

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…

We designed an asynchronous undergraduate introductory statistics course that focuses on simulation-based inference at the University of Nebraska-Lincoln. In this article, we describe the process we used to design the course and the structure of the course. We also discuss feedback and comments we received from students on the course evaluations,…

It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…

We developed an interactive online textbook that interleaves R programming activities with text as a way to facilitate students' understanding of statistical ideas while minimizing the cognitive and emotional burden of learning programming. In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as…

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…

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…

Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an essential element of a reproducible workflow that deserves due consideration among the learning objectives of statistics courses. This article describes experiences and…