The Statistical Modeling Group (SMG) is a unit within Analytic Studies & Institutional Research (ASIR) that utilizes a variety of statistical and predictive modeling frameworks to conduct research around high priority campus initiatives related to student success and the strategic priorities of the campus. SMG focuses on actionable outcomes and innovative solutions with predictive and prescriptive analytics that help drive student success at SDSU.
Recently published SMG research
- Assessing Instructional Modalities: Individualized Treatment Effects for Personalized Learning. Journal of Statistics Education.
- Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research. Practical Assessment, Research, and Evaluation.
- Random Forests for Evaluating Pedagogy and Informing Personalized Learning. Journal of Educational Data Mining.