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Katie A. McCarthy; Gregory A. Kuhlemeyer – Journal of Statistics and Data Science Education, 2024
To meet the demands of industry, undergraduate business curricula must evolve to prepare analytics-enabled professionals in fields such as finance, accounting, human resource management, and marketing. In this article, we provide a case study of developing a rigorous, integrated finance and data analytics course that was delivered using a…
Descriptors: Statistics Education, Finance Occupations, Course Content, Teaching Methods
Tucker, Mary C.; Shaw, Stacy T.; Son, Ji Y.; Stigler, James W. – Journal of Statistics and Data Science Education, 2023
We developed an interactive online textbook that interleaves R programming activities with text as a way to facilitate students' understanding of statistical ideas while minimizing the cognitive and emotional burden of learning programming. In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as…
Descriptors: Statistics Education, Undergraduate Students, Programming Languages, Student Attitudes
Thompson, JaCoya; Arastoopour Irgens, Golnaz – Journal of Statistics and Data Science Education, 2022
Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…
Descriptors: Data Analysis, Middle School Students, Statistics Education, Student Centered Learning