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Zachary del Rosario – Journal of Statistics and Data Science Education, 2024
Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…
Descriptors: Foreign Countries, Engineering Education, Engineering, Technical Occupations
Isabel R. Fulcher; Donald Fejfar; Nichole Kulikowski; Jean-Claude Mugunga; Michael Law; Bethany Hedt-Gauthier – Journal of Statistics and Data Science Education, 2024
During the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that…
Descriptors: Capacity Building, COVID-19, Pandemics, Public Health
Ciaran Evans; William Cipolli; Zakary A. Draper; John-Tyler Binfet – Journal of Statistics and Data Science Education, 2023
Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental…
Descriptors: Statistics Education, Learning Motivation, Undergraduate Students, Data Analysis
Christian Genest; James A. Hanley; Sahir R. Bhatnagar – Journal of Statistics and Data Science Education, 2024
This article provides an introduction to randomized response polling, a technique which was designed to allow for questioning on sensitive issues while protecting the respondent's privacy and avoiding social desirability bias. It is described in terms that are suitable for presentation and use in any classroom environment. Instructions for plain…
Descriptors: Foreign Countries, Randomized Controlled Trials, Controversial Issues (Course Content), Privacy
MacKay, Jon – Journal of Statistics and Data Science Education, 2022
Students need to know how to discern patterns and make decisions using visual information in our modern economy. However, there are few sources of real-world information available to instructors that give students access to visualizations to help develop their skills in interpreting complex situations using diverse data sources. This article…
Descriptors: Pandemics, COVID-19, Visual Aids, Data Analysis
Dennis Tay – Journal of Statistics and Data Science Education, 2024
Data analytics and programming skills are increasingly important in the humanities, especially in disciplines like linguistics due to the rapid growth of natural language processing (NLP) technologies. However, attitudes and perceptions of students as novice learners, and the attendant pedagogical implications, remain underexplored. This article…
Descriptors: Data Analysis, Programming, Linguistics, Graduate Students
Mayer, Benjamin; Kuemmel, Anja; Meule, Marianne; Muche, Rainer – Journal of Statistics and Data Science Education, 2023
Teaching practical skills is of particular interest in the study of human medicine. With regard to medical statistics this means the use of statistical software, which may be effectively taught by a flipped classroom approach. As a pilot study, we designed and implemented an elective course on medical statistics that focused on hands-on data…
Descriptors: Computer Software, Medicine, Statistics, Flipped Classroom
Ostblom, Joel; Timbers, Tiffany – Journal of Statistics and Data Science Education, 2022
In the data science courses at the University of British Columbia, we define data science as the study, development and practice of reproducible and auditable processes to obtain insight from data. While reproducibility is core to our definition, most data science learners enter the field with other aspects of data science in mind, for example…
Descriptors: Statistics Education, Data Science, Teaching Methods, Replication (Evaluation)
Polak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
Curley, Brenna; Peterson, Anna – Journal of Statistics and Data Science Education, 2022
In this article, we outline several activities revolving around soccer players who participated in the 2018 FIFA World Cup and 2019 FIFA Women's World Cup. Classroom activities are described from different perspectives, useful for a range of different statistics courses. In a first semester probability theory course, students investigate the…
Descriptors: Team Sports, Competition, Teaching Methods, Data Analysis
Althubaiti, Alaa – Journal of Statistics and Data Science Education, 2021
Today, most medical research depends on statistics, and interpreting these is crucial as the world tries to improve health outcomes. Medical students are at the front line in this effort but many have negative attitudes toward statistics. To assess this and offer recommendations, this study evaluates the attitudes of medical students in Riyadh,…
Descriptors: Foreign Countries, Medical Students, Student Attitudes, Medical Research