Enrollment Crystal Ball: Projections Simplified and Sophisticated

Session Abstract: Accurately predicting fall enrollment is crucial for effective planning and decision-making in higher education. This session explores a range of methodological approaches to enrollment projections, from simple ratio models to advanced logistic regressions. We will discuss how ratio-based models offer quick insights and are ideal for short-term estimates, while more complex techniques, such as logistic regression, can factor in key variables like scholarship dollars to provide deeper, data-driven forecasts. Attendees will learn the pros and cons of each approach and how to choose the best model for their institution's specific needs. Join us to discover how institutions can refine their enrollment forecasts to better align with strategic goals and make more informed decisions.

Keywords: enrollment projections, logistic regression, simple model, mixed model