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Amaliah, Dewi; Cook, Dianne; Tanaka, Emi; Hyde, Kate; Tierney, Nicholas – Journal of Statistics and Data Science Education, 2022
Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…
Descriptors: Statistics Education, Data Science, Textbooks, Data Analysis
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Towse, John; Davies, Rob; Ball, Ellie; James, Rebecca; Gooding, Ben; Ivory, Matthew – Journal of Statistics and Data Science Education, 2022
We advocate for greater emphasis in training students about data management, within the context of supporting experience in reproducible workflows. We introduce the "L"ancaster "U"niversity "ST"atistics "RE"sources (LUSTRE) package, used to manage student research project data in psychology and build…
Descriptors: Data Analysis, Information Management, Open Source Technology, Data Science
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Dogucu, Mine; Çetinkaya-Rundel, Mine – Journal of Statistics and Data Science Education, 2022
It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science…
Descriptors: Statistics Education, Data Science, Teaching Methods, Instructional Materials