Kelly McConville

Kelly McConville is the inaugural director of the Dominguez Center for Data Science. Before joining Bucknell, she served as the Co-Director of Undergraduate Studies for the Department of Statistics at Harvard University. Kelly has also taught at Reed College, Swarthmore College, and Whitman College and has held research appointments at the US Forest Inventory and Analysis Program and the US Bureau of Labor Statistics.

She is a Fellow of the American Statistical Organization and for several years has served as the Co-Program Chair of the US Conference on Teaching Statistics. Kelly enjoys helping students, faculty, and staff of all backgrounds develop their data acumen, learn statistical and computational tools, and build confidence in their quantitative abilities.

Educational Background

• Colorado State University, Ph.D. in Statistics
• Colorado State University, Masters in Statistics
• Olaf College, B.A. in Mathematics

Interests

• Data science and statistics education
• Survey statistics
• Machine learning and AI
• Data science communication

Interviews

Bailer, J. (2023) Live from USCOTS 2023 Part I. Stats + Stories Podcast. https:// statsandstories.net/education1/live-from-uscots-2023-part-1

Gladwell, M. (2021) Project Dillard. Revisionist History Podcast. https://www.pushkin. fm/episode/project-dillard/

Gladwell, M. (2021) Lord of the Rankings. Revisionist History Podcast. https://www. pushkin.fm/episode/lord-of-the-rankings/

Tarran, B. (2019) Voter ID Stats. Stats and Stories Podcast at JSM. https://statsandstories.net/politics1/voter-id-stats

Selected Publications and Software

McConville, K. S. (2025) Chapter 7: Multivariate Thinking. MAA Notes - Using

Data-Centric Methods to Teach Introductory Statistics, 99. https://maa.org/resource/notes-volume-99-using-data-centric-methods-to-teach-introductory-statistics/

White, G. W., Yamamoto, J. K., Elsyad, D. H., Schmitt, J. H., Korsgaard, N. H., Hu, J. K.,Gaines, G. C. III, Frescino, T. S. and K. S. McConville. (2025) Small area estimation of forest biomass via a two-stage model for continuous zero-inflated data. Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2024-0149

Toth, D. and McConville, K. S. (2024) Design consistent random forest models for data collected from a complex sample. Survey Methodology. 50(2), 185-207. http://www.statcan.gc.ca/pub/12-001-x/2024002/article/00015-eng.pdf

McConville, K. S., and I. Caldwell. (2020) pdxTrees: Data Package of Portland, Oregon Trees. R data package version 0.4.0. https://CRAN.R-project.org/package=pdxTrees

Nolan, J., McConville, K. S., Addona, V., Tintle, N., and D. Pearl. (2020) Mentoring Undergraduate Research in Statistics: Reaping the Benefits and Overcoming the Barriers. Journal of Statistics and Data Science Education. 28:2, 140 - 153. https://www.tandfonline.com/doi/full/10.1080/10691898.2020.1756542

McConville, K. S., Yamamoto, J., Tang, B., Zhu, G., Cheung, S., and S. Li. (2020) mase: Model-Assisted Survey Estimation. R package version 0.1.4 https://cran. r-project.org/package=mase

McConville, K. S., Stokes, L., and M. Gray. (2018) Accumulating Evidence of the Impact of Voter ID Laws: Student Engagement in the Political Process. Statistics and Public Policy, 5:1, 1-8. https://doi.org/10.1080/2330443X.2017.1407721

Website

mcconville.rbind.io