Andy Poppick

Education & Professional History

University of Chicago, BA, PhD

I received my PhD in the Department of Statistics at the University of Chicago in 2016, advised by Michael Stein and co-advised by Elisabeth Moyer.

Past Courses

• STAT 120 (formerly MATH 215): Introduction to Statistics (Autumn 2016, Spring 2017, Winter 2018, Spring 2018, Winter 2019, Spring 2019, Autumn 2020, Winter 2021)
• STAT 230 (formerly MATH 245): Applied Regression Analysis (Winter 2017, Autumn 2017, Autumn 2018)
• MATH 240 (formerly MATH 265): Probability (Winter 2018)
• STAT 250 (formerly MATH 275): Introduction to Statistical Inference (Spring 2017, Spring 2019, Winter 2021)
• STAT 285 (formerly MATH 280): Statistical Consulting (Autumn 2018, Winter 2019, Spring 2019)
  • Clients have included: College Possible, Community Action Center of Northfield, Hennepin County, Mathematical Association of America, Metro Transit, Northfield Public Schools
• STAT 320 (formerly MATH 315): Time Series Analysis (Spring 2018, Spring 2021)

Undergraduate Research Projects Supervised

• Jacob Flignor, Libby Nachreiner, Yicheng Shen, and Karen Wang (Autumn 2021 – Winter 2022). “Summer of Smoke? An Extreme Value Analysis of Air Pollution In Minnesota” (Senior Integrative Exercise)
• Sarah Grier, Waleed Iftikhar, Nate Isbell, and Muyang Shi (Winter – Spring 2021). “Quantile regression with applications in temperature and agricultural analysis” (Senior Integrative Exercise)
• Trevor Freeland, Pedro Girardi, and Joseph Nardi (Autumn 2018 – Winter 2019). “A statistical analysis of changes in extreme precipitation in the coastal Carolinas” (Senior Integrative Exercise)
• Noah Feldman and Joseph Nardi (Summer 2018). “A statistical analysis of compressed climate model data”
• Melissa Bain, Caitlin Eichten, Il Shan Ng, and Lianne Siegel (Winter – Spring 2017). “Estimating the uncertainty in temperature trends due to internal climate variability” (Senior Integrative Exercise)

Publications

• Poppick, A. (2023). Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach”. Journal of Agricultural, Biological and Environmental Statistics, 28(2), 345-348. journal
• Poppick A. & Stein M. L. (2022). Discussion on “A combined estimate of global temperature” by P. Craigmile and P. Guttorp. Environmetrics, 33(3): e2718. journal
• McKinnon, K. A., Poppick, A., & Simpson, I. R. (2021). Hot extremes have become drier in the US Southwest, Nature Climate Change, 11: 598-604. journal
• Schwarzwald, K., Poppick, A., Rugenstein, M., Bloch-Johnson, J., Wang, J., McInerney, D., & Moyer, E. J. (2021). Changes in future precipitation mean and variability across scales, Journal of Climate, 34(7): 2741-2758. journal
• Poppick A. & McKinnon, K. A. (2020). Observation-based simulations of humidity and temperature using quantile regression. Journal of Climate, 33(24): 10691-10706. journal
• Poppick, A., Nardi, J.*, Feldman, N.*, Baker, A. H., Pinard, A. & Hammerling, D. M. (2020). A statistical analysis of compressed climate data. Computers & Geosciences, 145: 104599. journal
• McKinnon, K. A. & Poppick, A. (2020). Estimating changes in the observed relationship between humidity and temperature using noncrossing quantile smoothing splines. Journal of Agricultural, Biological, and Environmental Statistics, 25(3): 292-314. journal
• McKinnon, K. A., Poppick, A., Dunn-Sigouin, E., & Deser, C. (2017). An ‘Observational Large Ensemble’ to compare observed and modeled temperature trend uncertainty due to internal variability. Journal of Climate, 30(19): 7585-7598. journal
• Poppick, A., Moyer, E. J., & Stein, M. L. (2017). Estimating trends in the global mean temperature record. Advances in Statistical Climatology, Meteorology and Oceanography, 3(1): 33-53. journal
• Klavans, J., Poppick A., Sun, S., & Moyer, E. J. (2016). The influence of model resolution on temperature variability. Climate Dynamics, 48(8): 3035-3045. journal
• Poppick, A., McInerney, D. J., Moyer, E. J., & Stein, M. L. (2016). Temperatures in transient climates: improved methods for simulations with evolving temporal covariances. Annals of Applied Statistics, 10(1): 477-505. journal
• Poppick, A. & Stein, M. L. (2014). Using covariates to model dependence in nonstationary, high-frequency meteorological processes. Environmetrics, 25(5): 293-305. journal

* indicates undergraduate coauthor

I grew up in the suburbs of New York City and lived in Chicago for ten years before moving to Minnesota. My partner, Brigit, is a clinical social worker. I have a twin sister, Laura, who is a science journalist and an older brother, Dan, who is a poet.

I enjoy reading, cooking, Minnesota winters, cross country skiing, rollerblading, and spending time with my cats Jane (calico) and Louise (tortie).