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Amelia McNamara – Journal of Statistics and Data Science Education, 2024
When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal…
Descriptors: Teaching Methods, Introductory Courses, Statistics Education, Programming Languages
André Coners; Benjamin Matthies; Carolin Vollenberg; Julian Koch – Journal of Statistics and Data Science Education, 2025
The proficient handling of data can undoubtedly be regarded as a key skill for the future. However, the need for data competencies is not limited to traditional professions in the information technology environment but is rather necessary across industries and work fields. Consequently, there is a call to integrate such Data Literacy and Data…
Descriptors: Statistics Education, Higher Education, Information Science Education, Computer Science Education
Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
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
Reinhart, Alex; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…
Descriptors: Computer Software, Graduate Students, Computer Science Education, Statistics Education
Liao, Shu-Min – Journal of Statistics and Data Science Education, 2023
SCRATCH, developed by the Media Lab at MIT, is a kid-friendly visual programming language, designed to introduce programming to children and teens in a "more thinkable, more meaningful, and more social" way. Although it was initially intended for K-12 students, educators have used it for higher education as well, and found it…
Descriptors: Teaching Methods, Coding, Programming Languages, Computer Science Education
Burckhardt, Philipp; Nugent, Rebecca; Genovese, Christopher R. – Journal of Statistics and Data Science Education, 2021
Revisiting the seminal 2010 Nolan and Temple Lang article on the role of computing in the statistics curricula, we discuss several trends that have emerged over the last ten years. The rise of data science has coincided with a broadening audience for learning statistics and using computational packages and tools. It has also increased the need for…
Descriptors: Statistics Education, Teaching Methods, Web Based Instruction, Data Analysis