Kari Lock Morgan is an Assistant Professor of Statistics at Penn State.
Lock Morgan received her Ph.D. in Statistics from Harvard University in 2011. She received her A.M. in Statistics from Harvard University in 2007, and a B.A. with Honors in Mathematics from Williams College in 2004.
Kari's research focuses on causal inference, statistics education, and simulation-based inference. A general theme throughout these three areas is that it is now computationally easy to generate thousands of randomizations instantly, and we can and should be taking advantage of this fact to collect better experimental data, to teach statistics in a way that leads to better conceptual understanding, and to more flexibly analyze data for statistical inference. Regarding causal inference, Kari focuses on obtaining comparable groups for causal comparisons, either by design in experimental settings, or by analysis in observational settings. For experiments she primarily works on the topic of rerandomization – the idea that we can improve covariate balance by rerandomizing treatment assignment if balance is not acceptable. For observational studies she primarily works with propensity score methodology. Regarding statistics education, Kari works primarily on improving introductory statistics education, particularly through the use of simulation-based inference, multivariable thinking, and data visualization. Regarding simulation-based inference, Kari conducts research on the effectiveness of these methods as pedagogical tools, and also on the general use of these methods as modern statistical methodology.
Kari Lock Morgan joined Penn State as an assistant professor in 2014, and has contributed most broadly to the field of statistics education. She currently serves on the ASA/MAA Joint Committee for Undergraduate Statistics Education, and has served on the executive committee for the ASA’s Section on Statistics Education, as the program chair for the Electronic Conference on Teaching Statistics (eCOTS), as the Associate Director for Professional Development for CAUSE (the Consortium for Advancement of Undergradute Statistics Education), and as a member of several other national statistics education committees and groups. She has given 28 invited talks or workshops on statistics education, including a plenary address at the 2019 United States Conference on Teaching Statistics and four invited talks at the International Conference on Teaching Statistics. She has also given 20 invited talks on causal inference.
Honors and Awards
- Robert V. Hogg Award for Excellence in Teaching Introductory Statistics (national, 2018)
- Teaching Statistics in the Health Sciences Best Paper Award (2017)
- Center for Excellence in Science Education (CESE) Tombros Education Fellow (2015)
- Dexter C. Whittinghill III Outstanding Contributed Paper Award in Statistics Education (2013)
- Derek C. Bok Award for Excellence in Graduate Student Teaching of Undergraduates (university-wide, 2010)
- Zhou, Q., Ernst, P.A., Lock Morgan, K., Rubin, D.B., & Zhang, A. (2018). “Sequential rerandomization,” Biometrika, 105(3): 745-752.
- Li, F., Lock Morgan, K., & Zaslavsky, A.M. (2018). “Balancing Covariates via Propensity Score Weighting,” Journal of the American Statistical Association (JASA), 113(521): 390-400.
- Lock, R.H., Lock, P.F., Lock Morgan, K., Lock, E.F., Lock, D.F. (2017). Statistics: Unlocking the Power of Data, 2e, John Wiley and Sons.
- Lock Morgan, K. and Rubin, D.B. (2015). “Rerandomization to Balance Tiers of Covariates,” JASA, 110(512):1412-1421.
- Lock Morgan, K., Lock, R., Lock, P.F., Lock, E.F., Lock, D.F. (2014). “StatKey: Online Tools for Bootstrap Intervals and Randomization Tests,” International Conference on Teaching Statistics (ICOTS) 9 Proceedings.
- Lock, R., Lock, P.F., Lock Morgan, K., Lock, E.F., Lock, D.F. (2014). “Intuitive Introduction to the Important Ideas of Inference,” ICOTS 9 Proceedings.
- Lock Morgan, K. and Rubin, D.B. (2012) “Rerandomization to Improve Covariate Balance in Experiments,” Annals of Statistics, 40(2): 1262-1282.
- Lock, K. and Gelman, A. (2010) “Bayesian Combination of State Polls and Election Forecasts,” Political Analysis, 18(3): 337-348.
- Cook, B, McGuire, T., Lock, K., Zaslavsky, A., (2010). “Comparing Methods of Racial and Ethnic Disparities Measurement across Different Settings of Mental Health Care,” Health Services Research, 45(3): 825-847.
- Morris, C.N. and Lock, K.F. (2009) “Unifying the Named Natural Exponential Families and their Relatives,” The American Statistician, 63 (3): 247-253.
STAT 597 - Causal Inference
STAT 250 - Introduction to Biostatistics
STAT 592 - Teaching Statistics
PSU 016 - First-Year Seminar