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Çetinkaya-Rundel, Mine; Dogucu, Mine; Rummerfield, Wendy – Statistics Education Research Journal, 2022
Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…
Descriptors: Introductory Courses, Data Analysis, Statistics Education, Units of Study
Çetinkaya-Rundel, Mine; Ellison, Victoria – Journal of Statistics and Data Science Education, 2021
The proliferation of vast quantities of available datasets that are large and complex in nature has challenged universities to keep up with the demand for graduates trained in both the statistical and the computational set of skills required to effectively plan, acquire, manage, analyze, and communicate the findings of such data. To keep up with…
Descriptors: Introductory Courses, Data Analysis, Statistics Education, Undergraduate Students
Beckman, Matthew D.; Çetinkaya-Rundel, Mine; Horton, Nicholas J.; Rundel, Colin W.; Sullivan, Adam J.; Tackett, Maria – Journal of Statistics and Data Science Education, 2021
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…
Descriptors: Statistics Education, Data Analysis, Teaching Methods, Graduate Students