Case Study: Virginia Tech achieves more robust interdisciplinary research with JMP

At Virginia Tech, collaborative research leads to a better understanding of species ecology

Virginia Tech’s Statistical Applications and Innovation Group (SAIG) needed a way to help graduate students in statistics gain practical experience while also supporting researchers from other disciplines with more robust analysis. In this case, Virginia Tech student Brandon Semel’s lemur ecology research involved a large, complex dataset with many missing values, multicollinearity, and lots of zeros, making it difficult to analyze effectively. JMP was used to support the statistical work.

With Virginia Tech, JMP helped the team build regularized linear models, combining lasso and ridge regression with the elastic net to identify important variables and estimate their effects. JMP also supported a zero-inflated Poisson approach for the non-normal data, making the analysis more manageable and repeatable. The result was a clearer understanding of the nutritional and ecological factors behind lemur geophagy, with insights that can help improve conservation strategy and captive rearing outcomes.

Virginia Tech

Brandon Semel

Virginia Tech