Three Principles for Modernizing an Undergraduate Regression Analysis Course
AbstractAs data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and de...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-05-01
|
| Series: | Journal of Statistics and Data Science Education |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/26939169.2023.2165989 |
| _version_ | 1797773334434283520 |
|---|---|
| author | Maria Tackett |
| author_facet | Maria Tackett |
| author_sort | Maria Tackett |
| collection | DOAJ |
| description | AbstractAs data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however, there has been less work beyond the first course. This article describes innovations to Regression Analysis taught at Duke University, a course focused on application that serves a diverse undergraduate student population of statistics and data science majors along with nonmajors. Three principles guiding the modernization of the course are presented with details about how these principles align with the necessary skills of practice outlined in recent statistics and data science curriculum guidelines. The article includes pedagogical strategies, motivated by the innovations in introductory courses, that make it feasible to implement skills for the practice of modern statistics and data science alongside fundamental statistical concepts. The article concludes with the impact of these changes, challenges, and next steps for the course. Portions of in-class activities and assignments are included in the article, with full sample assignments and resources for finding data in the supplemental materials. Supplementary materials for this article are available online. |
| first_indexed | 2024-03-12T22:04:56Z |
| format | Article |
| id | doaj.art-45d639fceb1d425cb6171d157ef1faa9 |
| institution | Directory Open Access Journal |
| issn | 2693-9169 |
| language | English |
| last_indexed | 2024-03-12T22:04:56Z |
| publishDate | 2023-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Statistics and Data Science Education |
| spelling | doaj.art-45d639fceb1d425cb6171d157ef1faa92023-07-24T16:50:04ZengTaylor & Francis GroupJournal of Statistics and Data Science Education2693-91692023-05-0131211612710.1080/26939169.2023.2165989Three Principles for Modernizing an Undergraduate Regression Analysis CourseMaria Tackett0Department of Statistical Science - Duke University, Durham, NCAbstractAs data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however, there has been less work beyond the first course. This article describes innovations to Regression Analysis taught at Duke University, a course focused on application that serves a diverse undergraduate student population of statistics and data science majors along with nonmajors. Three principles guiding the modernization of the course are presented with details about how these principles align with the necessary skills of practice outlined in recent statistics and data science curriculum guidelines. The article includes pedagogical strategies, motivated by the innovations in introductory courses, that make it feasible to implement skills for the practice of modern statistics and data science alongside fundamental statistical concepts. The article concludes with the impact of these changes, challenges, and next steps for the course. Portions of in-class activities and assignments are included in the article, with full sample assignments and resources for finding data in the supplemental materials. Supplementary materials for this article are available online.https://www.tandfonline.com/doi/10.1080/26939169.2023.2165989Course designEducationFlipped classroomReproducibilityStatistics curriculum |
| spellingShingle | Maria Tackett Three Principles for Modernizing an Undergraduate Regression Analysis Course Journal of Statistics and Data Science Education Course design Education Flipped classroom Reproducibility Statistics curriculum |
| title | Three Principles for Modernizing an Undergraduate Regression Analysis Course |
| title_full | Three Principles for Modernizing an Undergraduate Regression Analysis Course |
| title_fullStr | Three Principles for Modernizing an Undergraduate Regression Analysis Course |
| title_full_unstemmed | Three Principles for Modernizing an Undergraduate Regression Analysis Course |
| title_short | Three Principles for Modernizing an Undergraduate Regression Analysis Course |
| title_sort | three principles for modernizing an undergraduate regression analysis course |
| topic | Course design Education Flipped classroom Reproducibility Statistics curriculum |
| url | https://www.tandfonline.com/doi/10.1080/26939169.2023.2165989 |
| work_keys_str_mv | AT mariatackett threeprinciplesformodernizinganundergraduateregressionanalysiscourse |