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Sara Colando; Johanna Hardin – Journal of Statistics and Data Science Education, 2024
There is wide agreement that ethical considerations are a valuable aspect of a data science curriculum, and to that end, many data science programs offer courses in data science ethics. There are not always, however, explicit connections between data science ethics and the centuries-old work on ethics within the discipline of philosophy. Here, we…
Descriptors: Philosophy, Data Science, Ethical Instruction, Ethics
Yuanting Lu – Journal of Statistics and Data Science Education, 2023
Interactive web-based applets have proven effective in teaching statistics. This article presents new implementations of web-based applets primarily targeting a traditional introductory statistics course in two particular areas: (a) using real-time response data to engage students in simulations and (b) generating randomized datasets for…
Descriptors: Computer Oriented Programs, Simulation, Statistics Education, Teaching Methods
Anthony Underwood; Aidan Sichel; Emily C. Marshall – Journal of Statistics and Data Science Education, 2024
Economics has become increasingly empirical and, alongside this shift, has come more demand for improved transparency and reproducibility in empirical economic research. In this article, we distribute a survey to almost 1500 economics faculty from the top 161 liberal arts colleges with an economics major (according to U.S. News & World Report)…
Descriptors: Teaching Methods, Economics Education, Undergraduate Students, Liberal Arts
Kim, Albert Y.; Hardin, Johanna – Journal of Statistics and Data Science Education, 2021
We provide a computational exercise suitable for early introduction in an undergraduate statistics or data science course that allows students to "play the whole game" of data science: performing both data collection and data analysis. While many teaching resources exist for data analysis, such resources are not as abundant for data…
Descriptors: Data Collection, Data Analysis, Statistics Education, Undergraduate Students
Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding