A Data Segmentation Approach to Modeling Freshman Retention

Part of our Women in Data Science Series

“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 Veera software suite by Rapid Insight Senior Analyst, James Cousins, to build a model predicting freshman retention.

Sarah Caro, PhD
Senior Research Analyst
University of New Haven

James Cousins
Senior Statistical Analyst
Rapid Insight

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