Burcu Eke Rubini is an Assistant Professor of Decision Sciences at the Peter T. Paul College of Business and Economics, University of New Hampshire. She earned her Ph.D. in Statistics from Arizona State University. Her research focuses on statistical models for complex dependent data, social networks, and missing data imputation.
Ph.D., Statistics, Arizona State University
M.A., Economics and Finance, Southern Illinois University
M.S., Economics, Arizona State University
B.S., Economics, Middle East Tech Univ
Nonlinear Statistical Models
Time Series Analysis
Interpersonal Social Networks
ADMN 420: Business Statistics
ADMN 510: Business Statistics
ADMN 872: Predictive Analytics
ADMN/DS 898/768: Topics/Forecasting Analytics
DS 768: Forecasting Analytics
DS 768/898: Forecasting Analytics
DS 803: Fundamentals of Statistical
DS 805: Statistical Learning
DS 807: Unstructured Data
Grujić, J., Eke, B., Cabrales, A., Cuesta, J. A., & Sánchez, A. (2012). Three is a crowd in iterated prisoner's dilemmas: experimental evidence on reciprocal behavior.. Sci Rep, 2, 638. doi:10.1038/srep00638
Eke, B., & Kutan, A. M. (2009). Are International Monetary Fund Programs Effective?: Evidence from East European Countries. Eastern European Economics, 47(1), 5-28. doi:10.2753/eee0012-8775470101
Eke, B., & Kutan, A. M. (2005). IMF-Supported Programmes in Transition Economies: Are They Effective?. Comparative Economic Studies, 47(1), 23-40. doi:10.1057/palgrave.ces.8100090
Eke Rubini, B. (2020, September 30). Active Learning in Intro Statistics Classroom: Sampling Variability. In Women in Statistics and Data Science. Online.
Eke Rubini, B., & Rubini, L. (2022, August 6). A Mixed Model Approach for Dynamic Trade Networks. In Joint Statistical Meetings 2022. Washington, DC.
Eke Rubini, B., & Zifla, E. (2021, October 30). Evaluating Health-Related News Stories: A Mixed Approach that Combines Text Analysis and Machine Learning. In New England chapter of the Association of Information Systems (NEAIS) 2021 Conference. Boston, MA.