This post is part of the series, Women in Data Science. In this webinar series featuring Veera users, learn how women data scientists are driving change and making an impact at their organizations by way of data analysis and predictive modeling projects.
“One size fits all” doesn’t always work for predictive models. In this on-demand video, Sarah Caro shared her approach to developing multiple freshman retention models targeted toward unique segments of University of New Haven’s student population. Sarah discussed her findings and the trial and error process to identify key variables that affect retention differently for different student populations.
The presentation is followed by a brief demonstration of the software suite by Rapid Insight Senior Analyst, James Cousins, to build a model predicting freshman retention.