[R] Online course - Modeling in R

[Peter C. Bruce]

Drs. Brian Everitt and Torsten Hothorn will present their online course 
"Modeling in R" at statistics.com Jan. 19 - Feb. 16.   Participants can ask 
questions and exchange comments with Drs. Everitt and Hothorn via a private 
discussion board throughout the period.

In this course you learn how to use R to build statistical models and use 
them to analyze data. Multiple regression is covered first, then logistic 
regression and the generalized linear model (multiple regression and 
logistic regression illustrated as special cases). The Poisson model for 
count data, and the concept of overdispersion are also covered. You learn 
how to analyze longitudinal data using straightforward graphics and simple 
inferential approaches, then mixed-effects models and the generalized 
estimating approach for such data. The course emphasizes how to fit the 
models listed and interpret results, rather than how to derive the 
theoretical background of the models.

Brian Everitt and Torsten Hothorn are the authors of "A Handbook of 
Statistical Analyses Using R."  Brian Everitt is Professor Emeritus, King's 
College, London, and author of more than 50 books on statistics, including 
"Applied Multivariate Analysis" and "Statistical Aspects of the Design and 
Analysis of Clinical Trials."  Torsten Hothorn is Lecturer of Statistics at 
the Institut fur Medizininformatik, Biometrie und Epidemiologie, 
Friedrich-Alexander-Universitat, Erlangen-Nurnberg, Germany, and the author 
of over 4 dozen scholarly papers in peer-reviewed journals and other 
publications.

Details/prerequisites:
http://www.statistics.com/courses/modelingr/

The course takes place online at statistics.com in a series of 4 weekly 
lessons and assignments, and requires about 7-15 hours/week. Participate at 
your own convenience; there are no set times when you are required to be 
online.

Peter Bruce
pbruce at statistics.com