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Megan Heyman

Assistant Professor of Mathematics

Dr. Megan Heyman joins the department faculty after earning her doctorate in statistics by examining partial linear modeling. She is a Rose-Hulman alumna (minoring in optical engineering and economics) who has taught courses in data analysis, statistical theory, and applied multivariate in finite populations. Dr. Heyman completed research assistantships with NASA's Jet Propulsion Laboratory and the National Science Foundation (predicting Minnesota crop yields from climate information).

Teaching Interests

  • Statistics
  • Probability

Research Interests

  • Bootstrapping methods for spatio-temporal data
  • Modeling environmental data with nonparametric statistics

Select Publications & Presentations

  • Heyman, M. and Chatterjee, S., WiSEBoot: Wild Scale-Enhanced Bootstrap, R Package Version 1.4.0, 2016 
  • Braverman, A., Chatterjee, S., Heyman, M., and Cressie, N., Probabilistic Evaluation of Competing Climate Models, Being Published in 2016
  • Heyman, M. and Chatterjee, S., “Predicting Crop Yield via Partial Linear Model with Bootstrap,” Machine Learning and Data Mining approaches to Climate Science (Proceedings of the Fourth International Workshop on Climate Informatics), 2015

Academic Degrees

  • PhD, University of Minnesota, Statistics, 2016
  • MS, University of Minnesota, Statistics, 2014
  • BS, Rose-Hulman Institute of Technology, 2008