Bayesian Inference of Sample Surveys Date: 10th - 11th April 2006
Venue: Southampton Statistical Sciences Research Institute, University of Southampton Bayesian methods in statistics are increasingly popular, spurred by advances in computational power and tools. Bayesian inference provides solutions to problems that cannot be solved exactly by standard frequentist methods. Students learning the Bayesian approach will obtain new analysis tools and a deeper understanding of competing systems of statistical inference, including the frequentist approach. The objective of this course is to describe the application of the Bayesian approach to survey sampling, where the focus of inference is on finite population quantities. The instructor has conducted research in Bayesian methods, and has developed applications to real-world survey problems. Speakers Roderick Little is Richard D. Remington Collegiate Professor of Biostatistics and Research Professor, Survey Research Center at the University of Michigan. His areas of research expertise primarily focus on how to handle missing data in variety of statistical analyses, and inference from sample surveys. He has published numerous articles on these topics and was also the Coordinating and Applications Editor of JASA. He is the coauthor with Donald Rubin of an outstanding book entitled Statistical Analysis with Missing Data. He is the 2005 Wilks Award recipient from the American Statistical Association. Contact Jane Schofield ESRC National Centre for Research Methods School of Social Sciences University of Southampton Southampton SO17 1BJ Tel: 023 8059 4539 Fax: 023 8059 8908 Email: [email protected] Website: http://www.ncrm.ac.uk Hosted by the University of Southampton Jane Schofield Administrator ESRC National Centre for Research Methods Tel: +44 (0)2380 594539 Fax: +44 (0)2380 598908
