Yan Zhuang

Yan Zhuang specializes in the areas of sequential analysis, sampling strategies, sample size determination, and statistical inference. She also enjoys working with people from other disciplines to conduct interdisciplinary research. Her current interdisciplinary collaboration projects include violations of drinking water quality and Medicare quality analysis.

Research

Yan's research involves combinations of important topics and concepts including information, sufficiency, maximum likelihood estimation, ancillary complement, confidence interval estimation, and two-sample tests for comparisons.

During her Ph.D., she completed three refereed international journal publications on Methodology and Computing in Applied Probability, Sequential Analysis, and Journal of Japan Statistical Society respectively. She was invited to give talks at international conferences and workshops.

Currently, she is working on a project about two sample mean comparison problems of normal distribution. To solve this classic problem, she is going to construct decision rules for hypothesis tests with preassigned levels of type-I and type-II error probabilities, and she will develop the sampling rules for determining sample size that is required to perform such tests. She is truly hopeful that once the current work is completed, she will have ample opportunities to identify a class of problem, which can be handled and tend to be seen in referred international journals.

Moving forward, she is interested in big data area. She plans to work on those topics soon: sample size determination of big data regression problems and choosing the most efficient sub data without losing required accuracy of coefficient estimations.

Also, Yan worked as a consultant at the statistical consulting center of UCONN for almost two years, where she found her enthusiasm in statistical consulting. Currently, she is working on two interdisciplinary collaboration projects, one is about violations of drinking water, the other one is about Medicare quality and cost analysis.

Yan started teaching undergraduate courses as an instructor from her second year of the Ph.D. program at University of Connecticut, where she taught Introduction to Statistics during summers from 2016 to 2018 and Statistical Methods during apring and fall semesters from 2016 to 2018. At Connecticut College, she will teach Statistical Computing with R and Advanced Regression Techniques in the Fall 2018. In the near future, she expects to teach Mathematical Statistics, and is interested in developing new courses, such as Categorical Data Analysis, Data Science, and Statistical Inference.

Publications

• Mukhopadhyay, N.,and Zhuang,Y. (2016): On Fixed-Accuracy and Bounded Accuracy Confidence Interval Estimation Problems in Fisher’s “Nile” Example, Sequential Analysis, 35: 516-535. ?DOI: https://doi.org/10.1007/s11009-016-9529-0
• Mukhopadhyay, N. and Zhuang,Y. (2017): MLE, Information, Ancillary Complement, and Conditional Inference with Illustrations, Methodology and Computing in Applied Probability, 19: 615-629. DOI: http://dx.doi.org/10.1080/07474946.2016.1238264
• Mukhopadhyay, N. and Zhuang,Y. (2018). Purely Sequential and Two-Stage Bounded-Length Confidence Interval Estimation Problems in Fisher’s “Nile” Example. Journal of Japan Statistical Society, 47: 237-272.

Invited Talks

• On Fixed-Accuracy and Bounded Accuracy Confidence Interval Estimation Problems in Fisher’s “Nile” Example, the 8th International Workshop on Applied Probability (IWAP), Toronto, Canada, June 20-23, 2016.
• Purely Sequential and Two-Stage Bounded-Length Confidence Interval Problems in Fisher’s “Nile” Example, 2018 Joint Research Conference on Statistics in Quality, Industry, and Technology, Santa Fe, New Mexico, June 11-14, 2018.
• Two-Sample Tests of Hypotheses to Compare Normal Distributions: Unknown and Unequal Variances, 2018 NRC in Statistics and Probability, Burnaby, BC, Canada, July 26-28, 2018

Workshops

• Methods and Tools for Exploratory Data Analysis with R, The 3rd Statistical Consulting Services (SCS) Workshop Day Presentations, Storrs, Connecticut, May 10, 2018.
• Applied Survey Data Analysis, Statistical Consulting Services (SCS) Workshop, Storrs, Connecticut, November 8, 2017.