The team used a variety of statistical techniques to build predictive models of giving behavior, and they also used sophisticated high-dimensional clustering techniques to group donors according to similarity of demographic characteristics and university experience. A key finding was that high-giving and low-giving donors exist in every cluster, an insight which will aid the Development Office in constructing strategies to cultivate future donors.
- Stephen Bayer, Associate Vice President for University Development
- Nathalie Spring, Duke University Development
- Robert Calderbank, Director, iiD
- Sheng Jiang, Ph.D. student, Statistics
- Matthew Newman, Duke University Sociology
- Sonia Xu, Duke University Statistics
- Alexandra Zrenner, Duke University Economics
- All quantitative STEM
"The Data+ program was filled with intelligent people from all different fields, so it was a great learning experience. Furthermore, since we worked in teams, it taught me how to work with others in a more efficient, collaborative, and overall better level. Working to meet our clients' needs, I feel as if I gained real-world work experience in a classroom-like atmosphere (project mentor as my teacher, my group as the students). It is a great transition for people who are unsure of what they want to do with their careers or feel under-qualified to pursue a real internship."
-Sonia Xu, Duke University Statistics