Held on Wednesday, April 27th, 2011 at the Wyndham in Glenview, IL.
The 2011 Spring Workshop of the Northeastern Illinois Chapter of the American Statistical Association presents:
Principles of Statistical Design
presented by: George Casella, Ph.D., Professor of Statistics & Genetics Institute, University of Florida
Abstract
This course covers the principles and practice of statistical design, paying attention to the setup and implementation of an experiment, and the underlying theory that allows valid inferences. Such details are important in obtaining the proper error terms for treatment inferences in complicated designs.
The course will begin with a review of the basic tools for statistical design. The more common designs will be covered (factorial completely randomized designs, randomized complete blocks) and their variations (such as Latin squares). Emphasis is on designing the experiment to obtain the best inference on treatment contrasts, and the designs are illustrated will real data problems taken from many areas: agriculture, engineering, public health, etc. There is a focus on microarray designs, and we will spend time on split plots and their variations (crossover and repeated measures), and then move to confounding (incomplete blocks). These designs are form the basis of many microarray experiments. If time permits we can also discuss how to analyze data from these designs using the statistical package R.
The R programs and examples used in Dr. Casella's presentation are
available for download here.
Audience
The course is aimed at professional-level statisticians or interested faculty and graduate students. Attendees should have a working knowledge of statistical methodology and data analysis (for example from Rawlings et al. Applied Regression Analysis (1998, Springer-Verlag). The course is based on Dr. Casella's textbook Statistical Design (2008, Springer-Verlag).
Speaker Bio
George Casella is Distinguished Professor in the Department of Statistics, and Distinguished Member of the Genetics Institute, at the University of Florida. He is active in many aspects of statistics, having contributed to theoretical statistics in the areas of decision theory and statistical confidence, to environmental statistics, and has more recently concentrated efforts in statistical genomics and political science methodology. He also maintains active research interests in the theory and application of Monte Carlo and other computationally intensive methods. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and an Elected Fellow of the International Statistics Institute. He has been listed as an ISI "Highly Cited researcher", and has recently been elected Foreign Member of the Spanish Royal Academy of Sciences.
In other capacities, Casella has also served as Theory and Methods Editor of the Journal of the American Statistical Association, 1996-1999, Executive Editor of Statistical Science, 2002-2004, and is currently Joint Editor the Journal of the Royal Statistical Society, Series B. He has served on the Board on Mathematical Sciences of the National Research Council, 1999-2003, and many other committees of the American Statistical Association and the Institute of Mathematical Statistics. Casella has authored seven textbooks: Variance Components, 1992, with S. R. Searle and C. E. McCulloch; Theory of Point Estimation, Second Edition, 1998, with Erich Lehmann, Statistical Inference Second Edition, 2001, with Roger Berger; Monte Carlo Statistical Methods, Second Edition, 2004, with Christian Robert; Statistical Analysis of Quantitative Traits, 2007, with C. X. Ma and R. Wu, Statistical Design, 2008, and An Introduction to Monte Carlo Methods with R, with Christian Robert.