Applied Statistics Group

Main Focus of Research Interests

  • Statistical analysis of microarray data, and DNA sequence using Bayesian, meta-analytic and semi-parametric procedures
  • Bioinformatics
  • Large scale computer simulation
  • Modeling and analysis of clustered discrete data with applications to teratology and developmental toxicity studies
  • Statistical risk assessments based on clustered data
  • Random number generation
  • Design of experiment
  • Cryptography
  • Nonparametric and Semiparametric Statistics

Research Focus and Collaboration

The focus of our research is statistical applications. As such our faculty collaborate extensively with research groups within the university: faculty from Biology and Computer Sciences Departments, the College of Education, the School of Public Health, the College of Engineering, and the Fogelman College of Business and Economics. We stress the importance of graduate students' participation in faculty research and collaboration. To ensure that our graduate students get training in analyzing real life data, we have an established internship program for PhD students with the Department of Biostatistics at St. Jude Children's Research Hospital and occasionally with the University of Tennessee Health Sciences Center. Our graduate students also get practical experience through graduate assistantship support from other departments as needed.


The group holds regular research seminars with presentations from faculty and graduate students. Our statistics group and members of the biostatistics faculty from the St. Jude Children's Research Hospital form the backbone of the West Tennessee Chapter of the American Statistical Association (WTASA), an organization whose membership includes faculty and graduate students from the School of Public Health, and the University of Tennessee Health Sciences Center. The WTASA holds monthly meetings and seminars.

Recommended Courses

In addition to foundation courses in the theory of probability and statistical inference, we encourage every student to take courses in Bayesian Inference, Stochastic Processes, Linear, Generalized Linear and Non-linear Models, Design of Experiments, Statistical Computing, Statistical Programming in R and SAS.

Research Conferences

PhD students are encouraged to attend various conferences in their research areas. This is in addition to the conferences and seminars frequently hosted by the Department. Usually, graduate students presenting at conferences get some funding for travel, hotel and meals.

Job Placement

We have a most impressive record of placement of PhD students. Practically all our Masters and PhD graduates obtain employment in universities, industries, colleges or high schools. These include those who are currently employed at top institutions such as Universities of Florida, Maryland, Chicago and Tennessee. Some others have achieved executive positions in pharmaceutical, insurance, and financial industries. Among our masters graduates are heads of department in some of the top private high schools in Memphis.

Summer Funding

Summer funding may be available for some advanced PhD students.

Editorial Activities

Our faculty provide editorial services to top journals that include the Journal of the American Statistical Association, Journal of the Royal Statistical Society, Biometrika, Biometrics, Technometrics, Journal of Statistical Planning and Inference, Journal of Computational Statistics and Graphical Statistics, Statistics in Medicine, Annals of Statistics, and Annals of Statistical Mathematics and Bioinformatics.


Below are research interest and two representative or recent publications from each member.

Dale BowmanDale Bowman, Assistant Professor
Research Interests: Applied statistics

  1. On the Exact Correlation Structure of Exchangeable Multinomial Outcomes, with E.O. George, submitted to Biometrics (2013).
  2. Regression Models for Analyzing Clustered Binary and Continuous Outcomes under an Assumption of Exchangeability, Analysis of Mixed Data: Methods & Applications, Chapman & Hall/CRC Press, with E.O. George and Q. An (2013).
  3. Bowman, D. and George E.O. 2018, A Bayesian analysis of clustered discrete and continuous outcomes, Journal of Applied Statistics, 45, 438-449, DOI 10.1080/02664763.2017.1280003, Bowman, D. and George, E.O. (2018).
  4. Secure and Fast Encryption (SAFE) with classical random number generators, ACM Transactions on Mathematical Software, 44 (4):45:1-45:17, Deng, L.Y., Shiau, J.J., Lu, H.H.S. and Bowman, D. (2018).

Su ChenSu Chen, Assistant Professor
Research Interests: Non-parametric and semi-parametric statistics and applied statistics

  1. Chen, S. and Pokojovy, M. Modern and classical k-sample omnibus tests, Wiley Interdisciplinary Reviews: Computational Statistics (2018), e1418:1-12.
  2. Chen, S. Optimal Bandwidth Selection for Kernel Density Functionals Estimation, Journal of Probability and Statistics (2015), Vol 2015: 1-21.

Lih-Yuan DengLih-Yuan Deng, Professor
Research Interests: Random number generation and simulation

  1. Efficient computer search of large-order multiple recursive generators for pseudo-random number generators, Journal of Computational and Applied Mathematics, 236, 3228-3237, with Shiau, J.J. H. and Lu, H. H. S. (2012).
  2. Large-order multiple recursive generators with modulus 231−1, INFORMS Journal on Computing, 24(4), 636-647, with Shiau, J.J. H. and Lu, H. H. S. (2012).

E. Olúṣẹ́gun GeorgeE. Olúṣẹ́gun George, Professor; Graduate Coordinator (Statistics)
Research Interests: Modeling and analysis of clustered data, Bayesian procedures in bioinformatics and meta-analysis

  1. An Empirical Bayes Approach for Analysis of Diverse Periodic Trends in Time Course Gene Expression Data, Bioinformatics, 29, 182-188. with M. Kocak, S. Pyne, and S. Pounds, (2013).
  2. On the Use of Stochastic Ordering to Test for Trend with Clustered Binary Data, Biometrika, 95-108, with A. Szabo, (2010).

C YangChing-Chi Yang, Assistant Professor
Research Interests: Industrial and engineering statistics, dimensional analysis, response surface methodology, and data mining

  1. Ching-Chi Yang & Dennis K. J. Lin. Stochastic lead time with order crossover, Quality Technology & Quantitative Management, 16:5, 575-587 (2019).
  2. Ching-Chi Yang & Dennis K. J. Lin. A Note on Selection of Basis Quantities for Dimensional Analysis (submitted for publication)
  3. Ching-Chi Yang, Le Bao, Yunji Zhang, Dennis Lin, & Fuqing Zhang. Using a Bayesian Model Averaging Method to Improve Consensus Forecasts of Tropical Cyclone Tracks (under preparation)