
Kedai Cheng, Ph. D.
Assistant Professor of MathematicsContact Information
- kcheng@unca.edu
- 5195
- 313 Rhoades/Robinson Hall
Kedai Cheng was born and raised in Wuxi, Jiangsu, China. He attended Indiana University at Bloomington for his undergraduate, obtaining two Bachelor’s degrees in Mathematics and Economics, and a Master’s degree in Economics. Before joining the Mathematics department at University of North Carolina at Asheville, he pursued his doctoral degree at the Department of Statistics at the University of Kentucky. Kedai’s academic interests vary broadly, including but not limited to developing appropriate methodologies for analysis and predictions, and using statistical tools to analyze problems in multidisciplinary subjects such as Economics, Quality Control and Aviations.
Education
- B.A. of Economics, 2013, Indiana University Bloomington
- B.S. of Mathematics, 2013, Indiana University Bloomington
- M.S. of Economics, 2015, Indiana University Bloomington
- M.S. of Statistics, 2017, University of Kentucky
- Ph.D. of Statistics, 2020, University of Kentucky
Courses Taught
- Statistics STA-210: Introduction to Statistical Reasoning
- Statistics STA-210: Introduction to Statistical Reasoning
- Statistics STA-648 (Graduate Course): Regression Methods
- Statistics STA-621 (Graduate Course): Nonparametric Statistics
- Statistics STA-656 (Graduate Course): Statistical Quality Control
- Statistics STA-645 (Graduate Course): Computational Theory Data Visualization
- Statistics STA-646 (Graduate Course): Probability and Inference
- Statistics STA-569 (Graduate Course): Applied Statistical Methods
- Statistics STA-296: Statistical Methods and Motivations
- Statistics STA-210: Introduction to Statistical Reasoning
- Economics ECON-E331: International Trade
Professional Interests
Tolerance Regions, Time Series Analysis, Nonparametric Statistics and Methodology, Machine Learning Algorithms, Regression Analysis, Statistical Quality Control.
Selected Publications
Cheng, Kedai, and Derek S. Young. "Tolerance intervals for autoregressive models, with an application to hospital waiting lists." Applied Stochastic Models in Business and Industry 36.2 (2020): 268-282.