Sam Weerahandi
Samaradasa Weerahandi (born September 1, 1948) is a Fellow of the American Statistical Association.[1] A former professor, who is also known as Sam Weerahandi is currently employed by Pfizer, Inc. as a Senior Director. At his current and former employers, Pfizer, Time Warner, and Telcordia, he brought Statistical Practice in business management to new highs by developing advanced Business Analytics to optimize Business Processes, including Inventory Management, Pricing, and Optimization of Promotional tactics such as TV Ads. He also served as an Architect of the award-winning Business Analytics Portals of Time/Warner and Pfizer, on which Sales & Marketing teams heavily depend upon to make business decisions.
Weerahandi introduced a number of notions, concepts, and methods for statistical analysis of small samples based on exact probability statements, which are referred to as exact statistics.[2][3] Commonly known as Generalized Inference, the new concepts include generalized p-value, generalized confidence intervals, and generalized point estimation. These methods, which are discussed in the two books he wrote, have been found to produce more accurate inferences compared to classical methods based on asymptotic methods when the sample size is small or when large samples tends to be noisy.[4][5][6][7]
Sam Weerahandi also serves as a spokesperson for the Asian American community. In that role, he has been instrumental in enhancing the Diversity at American Statistical Association, and at companies that he has worked for.
Weerahandi received his PhD from University of British Columbia, Canada, and his Postgraduate Diploma in Statistics and B.Sc. from University of Sri Jayewardenepura, Sri Lanka.
Bibliography
- Exact Statistical Methods for Data Analysis”, Springer-Verlag, New York, 1995
- Generalized Inference in Repeated Measures", Wiley, New York, 2004
References
- ↑ 1996 (choose initial W and then click submit) http://www.amstat.org/awards/fellowslist.cfm
- ↑ http://informahealthcare.com/doi/abs/10.3109/9781439822463.088
- ↑ http://www.ucs.louisiana.edu/~kxk4695/Biometrics-2003.pdf
- ↑ Ananda, M. M. A. (2003). Confidence intervals for steady state availability of a system with exponential operating time and lognormal repair time. Applied Mathematics and Computation , 137, 499-509.
- ↑ Bebu, I., and Mathew, T. (2009). Confidence intervals for limited moments and truncated moments in normal and lognormal models. Statistics and Probability Letters, 79, 375-380
- ↑ Hanning, J., Iyer, H., and Patterson, P. (2006). Fiducial generalized confidence intervals. Journal of the American Statistical Association, 101, 254-269.
- ↑ Lee, J. C., and Lin, S. H. (2004). Generalized confidence intervals for the ratio of means of two normal populations. Journal of Statistical Planning and Inference, 123, 49-60.
- Tsui, K., and Weerahandi, S. (1989). Generalized p-Values in Significance Testing of Hypotheses in the Presence of Nuisance Parameters. JASA, 18, 586-589.
- Weerahandi, S. (1993). Generalized Confidence Intervals. JASA, 88, 899-905.
- Weerahandi, S. (2012). General Point Estimation, Communications in Statistics T&M, 41, 4069-
- Tian, L. (2008). Generalized Inferences on the Overall Treatment Effect in Meta-analysis with Normally Distributed Outcomes, Biometrical Journal, 50, 237-247.
- Mu, W., and Wang, X. (2014). Inference for One-Way ANOVA with Equicorrelation Error Structure, The Scientific World Journal.
- Xiong S. (2011). An asymptotics look at the generalized inference, Journal of Multivariate Analysis, 102, 336–348.
- Wu, J.F., and Hamada, M.S. (2009). Experiments: Planning, Analysis, and Optimization, Wiles Series in Probability and Statistics.
- Krishnamoorthy, K., and Mathew, T. (2009). Statistical Tolerance Regions, Wiley Series in Probability and Statistics.