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Bagui,Subhash_211

Dr. Subhash C. Bagui

  • Position: Distinguished University Professor
  • Department: Mathematics and Statistics
  • Office Location: Building 4, Room 341
  • sbagui@uwf.edu
  • Campus: 8504742286

Biography

Dr. Subhash C. Bagui, a Professor in the Department of Mathematics and Statistics, has written books and published numerous articles. Bagui’s book is titled “Handbook of Percentiles in the Non-Central t-distributions.” Bagui, who has a Ph.D. in Statistics from the University of Alberta, Canada, conducts research on nonparametric classification/discrimination, statistical pattern recognition, and cluster analysis. These techniques have applications in cancer detection, gene identification, and DNA microarray data. He also examines aspects of data mining, biostatistics, design, and analysis of experiments, statistical computing and applied statistics. 

In addition, he has published findings for statistics education in K-12. His work has appeared in International Journal of Science and Research, Journal of Statistical Theory and Applications, and dozens of other publications. Bagui, who joined UWF in 1990, holds a B.S. in Statistics from the University of Calcutta, India, and two degrees from the Indian Statistical Institute – a Master’s in Statistics and a Post-Graduate Diploma in Statistical Quality Control and Operations Research. He has been an editor or editorial board member of several peer-reviewed publications and has reviewed papers proposed for other journals as well. Among his honors: Bagui won a UWF Faculty Catalyst Initiative Award in 2013-14.

Degrees & Institutions

Ph.D., Department of Statistics and Applied Probability, University of Alberta
Post Graduate Diploma in Statistical Quality Control and Operations Research, Indian Statistical Institute
M.S. Statistics, Indian Statistical Institute
B.Sc., Statistics/Honors, University of Calcutta

Research

My main research interests are in the areas of nonparametric classification/discrimination, statistical pattern recognition, and cluster analysis. These techniques have applications in cancer detection, gene identification, and DNA microarray data. Other areas of research that I work in are data mining, biostatistics, design and analysis of experiment, statistical computing and applied statistics. I would like to establish a research program that would fund recruiting students, increasing enrollment and graduation rates in STEM areas.

Keywords: non-central t-distributions, probability and distribution theory, nonparametric classification/discrimination, statistical pattern recognition, cluster analysis, biostatistics, statistical computing, applied statistics, K-12 statistics education