The Statistics and Data Science Fellows Program was launched in the Fall of 2014 with an inaugural group of six Fellows to help support statistics and data science at the college. The program has grown to a set of ten Fellows. The Fellows are ideally selected early in their time at Amherst in a “tiered” system so that students at all levels of the program can be involved and students have multiple years to develop their skills and acquire experience. The Fellows work during the academic year to support the Statistics program at Amherst in several distinct ways, with a variety of responsibilities dependent on their experience. As part of an ongoing group, they also end up supporting one another, which capitalizes on the tiered system with more senior Fellows mentoring more junior Fellows.
The Fellows work to support statistics and data analysis in several ways. First, all Fellows provide drop-in statistics and data science tutoring (for introductory and intermediate statistics, software support for R/RStudio/Quarto/GitHub, data management, data wrangling, and data visualization). In addition, the Fellows take on an additional project that can vary from semester to semester. Examples of current projects include:
- serving as a teaching assistant for a statistics or data science elective to enhance student learning and assist with computing in the course
- creating workshops for the campus and Five College community about data wrangling, graphical displays, and reproducible analysis
- providing statistics and data science consulting support, under the direction of the Statistics faculty
- working on special projects (e.g. support for the sports analytics program, Sustainability Office, Institutional Research, or other College entities) under the direction of the Statistics faculty
The Fellows meet on a monthly basis with the Statistics faculty for informal mentoring, review of issues and problems, training workshops, and to share updates on projects.
Fellows are selected from a competitive applicant pool. Requirements include completion of introductory and intermediate statistics (STAT230) and data science (STAT231), and general interest in pursuing statistics. The major in statistics is not required.
The inaugural year of the program was funded by the Dean of the Faculty. The program is now generously supported by the David and Jeanette Rosenblum Fund for Statistics and Data Science Fellows.
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