Publication Date
| In 2025 | 1 |
| Since 2024 | 7 |
Descriptor
Source
| Journal of Statistics and… | 7 |
Author
| Ainsley Miller | 1 |
| Allison S. Theobold | 1 |
| Amelia McNamara | 1 |
| Anne U. Gold | 1 |
| Brett Alberts | 1 |
| Charles Jason Tinant | 1 |
| David Parr | 1 |
| Dennis Tay | 1 |
| Elisha Yellow Thunder | 1 |
| Elsa Culler | 1 |
| Emily Biggane | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 7 |
| Reports - Research | 5 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 5 |
| Postsecondary Education | 5 |
Audience
Location
| Colorado | 1 |
| Hong Kong | 1 |
| United Kingdom (Scotland) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkAllison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Lucy D'Agostino McGowan; Travis Gerke; Malcolm Barrett – Journal of Statistics and Data Science Education, 2024
This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…
Descriptors: Statistics Education, Programming Languages, Statistical Inference, Causal Models
Ainsley Miller; Kate Pyper – Journal of Statistics and Data Science Education, 2024
R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…
Descriptors: College Freshmen, Undergraduate Study, Anxiety, Programming Languages
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
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
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
Nathan A. Quarderer; Leah Wasser; Anne U. Gold; Patricia Montaño; Lauren Herwehe; Katherine Halama; Emily Biggane; Jessica Logan; David Parr; Sylvia Brady; James Sanovia; Charles Jason Tinant; Elisha Yellow Thunder; Justina White Eyes; LaShell Poor Bear/Bagola; Madison Phelps; Trey Orion Phelps; Brett Alberts; Michela Johnson; Nathan Korinek; William Travis; Naomi Jacquez; Kaiea Rohlehr; Emily Ward; Elsa Culler; R. Chelsea Nagy; Jennifer Balch – Journal of Statistics and Data Science Education, 2025
Today's data-driven world requires earth and environmental scientists to have skills at the intersection of domain and data science. These skills are imperative to harness information contained in a growing volume of complex data to solve the world's most pressing environmental challenges. Despite the importance of these skills, Earth and…
Descriptors: Electronic Learning, Earth Science, Environmental Education, Science Education
