Megan Heyman

Hi, I'm Megan!

I joined the Rose-Hulman Mathematics Department in 2016 after completing my PhD in Statistics at the University of Minnesota. Areas of interest in my research include bootstrapping techniques, wavelets, and statistical modeling. I tend to be attracted to analyzing data with spatio-temporal structures.

Indiana MAA Fall Meeting, 2026

Creating Graphs That Tell Your Story

Infusing Sustainability Concepts into Mathematics and Statistics Courses

Professional Documents

CV

Upper Level Course Advertisements

MA 382

MA 480 Time Series

MA 481

MA 485

MA 487

R Packages

lmboot https://CRAN.R-project.org/package=lmboot

WiSEBoot https://CRAN.R-project.org/package=WiSEBoot

R Shiny

https://meganheyman.shinyapps.io/PIPO_TreeRingCor/
The "North American Ponderosa Pine Tree-Ring Width Records" applet allows visualization of spatial and temporal relationships among tree-ring records for pinus ponderosa.

SWB Seminar, University of Lagos: August 18, 2026

SWB Seminar Slides

R code for Taylor Swift album tracks example

R code for ocean microplastics additional example

Dataset for ocean microplastics additional example

MA Seminar 2026

Basketball Case Study Worksheet

Cellphone Case Study Worksheet

Seminar Slides

JSM 2025 Page

USCOTS 2025 Page

JSM 2019 Links and Documents

lmboot R Package Documentation

Save the Science Poster

Cruise Ship Example Dataset

Cruise Ship Example Code

Slides for lmboot package

IRSA Short Course Documents

Example R Code
Terre Haute Climate csv dataset (large)
Vostok Ice Core csv dataset
Slides

Minnesota Crop Yields

Minnesota Corn Yield 1923 - 2013

YouTube link (in case the video does not appear on this website): https://youtu.be/auV1LMkjcTc
*Visualization won University of Minnesota's U-Spatial Mapping Prize – “Graduate Student – Most Provocative/Transformative”

Minnesota Soybean Yield 1941 - 2013

YouTube link (in case the video does not appear on this website): https://youtu.be/UrMlfsa1lJM

The original crop yield data are available from http://quickstats.nass.usda.gov/. The climate variables used to predict crop yield in the Machine Learning and Data Mining approaches to Climate Science chapter are originally from https://mygeohub.org/groups/u2u/acv. The compiled Excel versions I used within Esri ArcMAP and within the chapter are also provided below. Any user of these datasets should cite the original source.