Principles of statistical design, 10am-4.30pm, Monday 13 September 2010
at the Holiday Inn in Brighton
Presented by George Casella (Department of Statistics and Genetics
Institute, University of Florida) 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 and the statistical package R. 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 major focus on microarray designs, and we will spend a
lot of time on split plots and their variations (strip plot, repeated
measures), and then move to confounding (incomplete blocks, fractions).
These designs are form the basis of many microarray experiments.
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 Springer- Verlag 1998).
The course is based on Professor Casella's text Statistical Design
(2008, Springer-Verlag)
The course forms part of the pre-conference courses and workshops
programme at the RSS 2010 Conference in Brighton - information about
registration can be found here: http://www.rss.org.uk/main.asp?page=3192
Paul Gentry
Theme Manager, Meetings & Conferences
Royal Statistical Society
Direct Tel. (020) 7614 3918
Fax. (020) 7614 3905
Register online for RSS 2010 Conference: www.rss.org.uk/rss2010
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