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Hairui Yu; Suzanne E. Perumean-Chaney; Kathryn A. Kaiser – Journal of Statistics and Data Science Education, 2024
Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…
Descriptors: Statistics Education, Data Science, Data Use, Research Problems
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Dogucu, Mine; Johnson, Alicia A.; Ott, Miles – Journal of Statistics and Data Science Education, 2023
Despite rapid growth in the data science workforce, people of color, women, those with disabilities, and others remain underrepresented in, underserved by, and sometimes excluded from the field. This pattern prevents equal opportunities for individuals, while also creating products and policies that perpetuate inequality. Thus, it is critical…
Descriptors: Access to Information, Inclusion, Instructional Materials, Statistics Education
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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