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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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Vilhuber, Lars; Son, Hyuk Harry; Welch, Meredith; Wasser, David N.; Darisse, Michael – Journal of Statistics and Data Science Education, 2022
We describe a unique environment in which undergraduate students from various STEM and social science disciplines are trained in data provenance and reproducible methods, and then apply that knowledge to real, conditionally accepted manuscripts and associated replication packages. We describe in detail the recruitment, training, and regular…
Descriptors: Statistics Education, Data Science, STEM Education, Social Sciences
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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