Department of Statistical Science

The Department of Statistics, which is located in the University’s Fox School of Business and Management, has 15 full-time graduate faculty members and about forty graduate students in its Master’s and Ph.D. programs.

Research Areas

Bayesian/Empirical Bayesian Statistics


Biostatistics


Experimental Design


High Dimensional Statistics


Multiple Testing


Nonparametric Statistics for Small and Big Data


Statistical Applications


Statistical Computing


Time Series Analysis


The Fox School’s Department of Statistics faculty is outstanding. Eight are elected Fellows of the American Statistical Association; five are elected members of the International Statistical Institute, three are Fellows of the Royal Statistical Society, and two are Fellows of the Institute of Mathematical Statistics. They publish extensively in a variety of areas: biostatistics and survival analysis; categorical data analysis; time series; nonparametric statistics; multiple testing, Bayesian methods, statistical genetics, big data dimension reduction, data mining, computational statistics; design of experiments; statistical graphics; bioequivalence studies;; statistical software design; and nonlinear mixed effect models. A list below of their books on advanced topics is a reflection of their expertise and varied interests.

In addition to several others, four faculty members have been awarded National Science Foundation research grants.


Books by Statistics Faculty

  1. Altan, S. and Singh, J. (Eds.) Recent Advances in Experimental Designs and Related Topics. Papers Presented at the Conference in Honor of Professor Damaraju Raghavarao Nova Science Publishers, 2001
  2. Ashanullah, M., Kennyon, J. and Sarkar, S. K. (Eds.) Applied Statistical Science V, Nova Science Publishers, Inc., New York, 2001.
  3. Benjamini, Y., Bretz, F. and Sarkar, S. K. (Eds.) Recent Developments in Multiple Comparison Procedures, IMS Lectures Notes- Monograph Series, Volume 4, 2004.
  4. Desu, M. M. and Raghavarao, D. Sample Size Methodology, Academic Press, 1990
  5. Desu, M. M. and Raghavarao, D. Nonparametric Statistical Methods for Complete and Censored Data, Chapman & Hall/CRC, 2003.
  6. Gonick, L. and Smith, W. The Cartoon Guide to Statistics, Harper Collins Publishers, 1993.
  7. Gucula, Jr., M. and Singh, J. Statistical Methods in Food and Consumer Research, Academic Press, 1984 (First Edition), 2006 (Second Edition)
  8. Heiberger, R. M. Computation for the Analysis of Designed Experiments. Wiley, 1989.
  9. Heiberger, R. M. and Holland, B. Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS, Springer-Verlag, 2004.
  10. Iglewicz, B. and Hoaglin, D. How to Detect and Handle Outliers, Quality Press, 1993.
  11. Iglewicz, B. and Stoyle, J. An Introduction to Mathematical Reasoning, MacMillan, 1973.
  12. Izenman, Alan J. Series: Modern Multivariate Statistical Techniques, Springer Texts in Statistics, 2008.
  13. Raghavarao, D. Constructions and Combinatorial Problems in Design of Experiments, Wiley, 1971; Dover, 1988.
  14. Raghavarao, D. Matrix Theory, Oxford & IBH Publishing, 1972.
  15. Raghavarao, D. Statistical Techniques in Agricultural and Biological Research, Oxford & IBH Publishing, 1983.
  16. Raghavarao, D. Exploring Statistics, Marcel Dekker, 1988.
  17. Raghavarao, D. and Padgett, L. V. Block Designs: Analysis, Combinatorics and Applications, World Scientific Publishing, 2005.
  18. Raghavarao, D., Wiley, J. B., and Chitturi, P. Choice-based Conjoint Analysis: Models and Designs (pp. 180 pages). Boca Raton, Florida: Chapman and Hall Publisher. 2010
  19. Wei, W. W. S. Time Series Analysis: Univariate and Multivariate Methods, Addison Wesley, 1990 (First Edition); Pearson/Addison Wesley, 2005 (Second Edition).