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Ann M. Brearley; Kollin W. Rott; Laura J. Le – Journal of Statistics and Data Science Education, 2023
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…
Descriptors: Statistics Education, Data Interpretation, Teaching Methods, Biology
Bertrand Schneider; Joseph Reilly; Iulian Radu – Journal for STEM Education Research, 2020
In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…
Descriptors: Learning Analytics, Classroom Techniques, Multimedia Materials, Graduate Students
Reinhart, Alex; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
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…
Descriptors: Computer Software, Graduate Students, Computer Science Education, Statistics Education