Teaching

I enjoy helping my students develop their abilities to think statistically, to understand variability, and to draw sound conclusions from data. The statistical software package R/RStudio plays a prominent role in most of my classes with the students learning a reproducible workflow through creating R Markdown reports.

Fall 2020 Courses:

  • Math 141: Introduction to Probability and Statistics
    • Students can access the RStudio Server here.

Spring 2020 Courses:

  • Math 343: Statistics Practicum
  • Math 241: Data Science
    • Course Slides can be found here

Research

I am a survey statistician and a data scientist whose scholarly activities include survey methodological developments, integrative research, applied statistical work, and software development. I greatly enjoy collaborative work and have active collaborations with the US Bureau of Labor Statistics and the US Forest Inventory and Analysis Program. For the past two summers, I have run the Reed Forestry Data Science Research Lab, a joint effort supported by Reed College, the US Forest Inventory and Analysis Program, and Swarthmore College.

Current Projects:

  • Within the Reed Forestry Data Science Lab:

  • Domain estimation and calibration using regression trees.

    • Collaboration with Daniell Toth (BLS).

Publications and Technical Reports:

  • Basil, M. R. K., Huque, S., McConville, K. S., Moisen, G. G., and T. S. Frescino. (In Press) Creating Homogeneous Landfire Vegetation Classes for Forest Inventory Applications in the Interior West. Gen. Tech. Rep. US. Department of Agriculture, Forest Service, Southern Research Station.
  • Rintoul, M. A., Maebius, S, Alvarado, E, Lloyd-Damnjanovic, A., Toyohara, M., McConville, K. S., Moisen, G. G., and T. S. Frescino. (In Press) An Alternative Post-Stratification Scheme toDecrease Variance of Forest Attributes in the Interior West. Gen. Tech. Rep. US. Department of Agriculture, Forest Service, Southern Research Station.
  • Moisen, G.G., McConville, K. S., Schroeder, T. A., Healey, S. P., Finco, M. V., and T. S. Frescino. (2020) Estimating Land Use and Land Cover Change in North Central Georgia: Can Remote Sensing Observations Augment Traditional Forest Inventory Data? Forests 11(8), 856, https://doi.org/10.3390/f11080856
  • Nolan, J., McConville, K. S., Addona, V., Tintle, N., and D. Pearl. Mentoring Un- dergraduate Research in Statistics: Reaping the Benefits and Overcoming the Barriers. Journal of Statistics Education. DOI: https://www.tandfonline.com/doi/full/10. 108010691898.2020.1756542
  • McConville, K. S., Moisen, G. G., and T. S. Frescino. (2020) A Tutorial on Model-Assisted Estimation with Application to Forest Inventory. Forests, 11(2), 244, https://doi.org/10.3390/f11020244
  • McConville, K. S. and D. Toth. (2019) Automated Selection of Post-Strata using a Model-Assisted Regression Tree Estimator. Scandinavian Journal of Statistics. https://doi.org/10.1111/sjos.12356
  • 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, https://doi.org/10.1080/2330443X.2017.1407721.
  • McConville, K. S., Breidt, F. J., Lee, T. C. M., and G. Moisen (2017). Model-Assisted Survey Regression Estimation with the Lasso. Journal of Survey Statistics and Methodology 5, 131-158.
  • McConville, K. S. and F. J. Breidt (2013). Survey Design Asymptotics of the Model-Assisted Penalised Spline Regression Estimator. Journal of Nonparametric Statistics 25, 745-763.
  • Ayala, J., Corbin, P., McConville, K., Colonius, F., Kliemann, W., and J. Peters (2006). Morse Decompostion, Attractors, and Chain Recurrence. Proyecciones Journal of Mathematics 25, 79-109.

It is raining stats and dogs.

The Reed Forestry Data Science Lab has been hard at work for a month now! The lab, supported by the US Forest Service Forest Inventory and Analysis Program, Reed College, and Swarthmore College, has 6 projects going this summer. These projects include: Creating interactive web dashboards of important forest estimates using FIESTA Exploring alternative variance estimators for data collected under a spatially systematic sampling design Producing forest inventory teaching materials Improving and expanding pdxTrees, an R data package of Portland park trees Increasing the functionality of mase, an R package of modern survey estimators Determining the utility of the generalized regression estimator for estimating forest attributes in the Interior West I asked each lab member to provide a picture of themselves with a tree and a description.

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I am teaching Math 241: Data Science this spring. As part of the course, the students are writing blog posts which can be found at reed.edu/math/241. The first batch are up and showcase some of the awesome data packages they have made.

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Over the course of 10 weeks, I had the pleasure of working with 6 awesome student researchers. We worked on SEVEN different projects related to data questions poised by the US Forest Service Forest Inventory and Analysis Program (FIA). This work was a joint collaboration between FIA, Reed College and Swarthmore College and therefore it involved 3 FIA folks: Gretchen Moisen, Research Scientist Tracey Frescino, Forester Chris Toney, Forester Four Reedies:

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I had the wonderful (and terrifying) experience of being interviewed by THE Significance magazine editor, Brian Tarran, about my work estimating the impacts of voter ID laws. Significance teamed up with the always amazing Stats + Stories to provide coverage on JSM 2019. You can listen to the interview here.

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