Assistant Director The University of West Florida, United States
Session Abstract: In this session, we will explore the relationship between student performance and gym attendance at the University of West Florida (UWF) Health and Leisure Sports (HLS) Facility using logistic regression with hyperparameter tuning. Attendees will learn how predictive models can be leveraged to assess student success through the lens of campus facility usage. We will cover the complete data analysis pipeline and showcase how R Shiny was used to visualize the results and make the insights actionable for stakeholders. Key takeaways include understanding how to apply machine learning techniques like logistic regression to real-world datasets, the value of hyperparameter tuning for model accuracy, and the power of interactive data visualizations for engaging nontechnical audiences. This session is ideal for institutional researchers and data scientists interested in the intersection of student outcomes and campus resources.
Keywords: data science, data analytics, R Shiny, data visualization, statistics
