Professor

Jie Peng, PhD

Dr. Jie Peng is a Professor in the Department of Management at St. Ambrose University. Dr. Peng has developed a wide array of undergraduate and graduate quantitative business courses to teach in the College of Business. Her teaching and research expertise includes Business Statistics, Business Analytics, Quantitative Research and Decision Science.

As an accomplished researcher, Dr. Peng has published in academic journals such as Communications in Statistics - Theory and Methods, Journal of Statistical Simulation and Computation, Journal of Applied Statistical Science, Journal of Occupational and Industrial Hygiene, Journal of Statistical Planning and Inference, and Communications in Statistics - Simulation and Computation. She has also presented her research at varied academic conferences.

She is a member of the American Statistical Association (ASA), Institute of Mathematical Statistics (IMS), International Chinese Statistical Association (ICSA), The Institute for Operations Research and the Management Sciences (INFORMS), and the Decision Sciences Institute (DSI).

Contact Us

Contact Jie Peng for information on Management

McMullen Hall 217C

563-333-6426

PengJie@sau.edu

Education and Training

PhD, University of Louisiana at Lafayette, Statistics
MS, University of Louisiana at Lafayette, Mathematics
MS, University of New Orleans, Louisiana, Statistics

Recent Publications

Peng, J. (2020). The Wald method versus the score method. Invited talk given at the Math/Statistics Colloquium at University of Louisiana, Lafayette, LA.
Peng, J. (2019). Improved prediction intervals for discrete distributions. Paper presented at the International Conference on Statistical Distributions and Applications (ICOSDA), Grand Rapids, MI.
Peng, J. (2018). Approximate one-sided tolerance limits in random effects model and in some mixed models and comparisons (updated). Paper presented at the ICSA China Conference on Data Science, Shandong, China.
Krishnamoorthy, K., Mathew, T., & Peng, J. (2016). A simple method for assessing occupational exposure via the one-way random effects model. Journal of Occupational and Industrial Hygiene, 13, 894-903.
Krishnamoorthy, K., Peng, J., & Zhang, D. (2016). Modified large sample confidence intervals for Poisson distributions: Ratio, weighted average and product of means. Communications in Statistics - Theory and Methods, 45, 83-97.
Peng, J. (2016). A simple method for assessing occupational exposure via the one-way random effects model. Paper presented at the Joint Statistical Meetings, Chicago, IL.
Krishnamoorthy, K., & Peng, J. (2015). Approximate one-sided tolerance limits in random effects model and in some mixed models and comparisons. Journal of Statistical Simulation and Computation, 85, 1651-1666.
Peng, J. (2015). Multiple comparison procedures for binomial distributions. Invited talk given at the Lafayette Mathematics Roeling Conference at the University of Louisiana, Lafayette, LA.
Peng, J. (2011). Multiple comparison procedures for binomial distributions. Proceedings of the Joint Statistical Meetings.
Peng, J., & Krishnamoorthy, K. (2011). Conditional and unconditional tests for comparing several Poisson means. Journal of Applied Statistical Science, 18(3), 1-8.
Krishnamoorthy, K., & Peng, J. (2010). Closed-form approximate prediction intervals for binomial and Poisson distributions. Journal of Statistical Planning and Inference, 141, 1709-1718.
Krishnamoorthy, K., & Peng, J. (2008). Exact properties of a new test and other tests for differences between several binomial proportions. Journal of Applied Statistical Science, 16, 23-35.
Krishnamoorthy, K., & Peng, J. (2007). Some properties of the exact and score methods for a binomial proportion and sample size calculation. Communications in Statistics - Simulation and Computation, 36, 1171-1186.