The original appeal of R (free, open-source, powerful) was in
academia. High-end enhancements now bring R's appeal to
businesses like Bank of America, Merck, Axciom and more
(Revolution Analytics, headed by SPSS pioneer Norman Nie,
is one company leading this effort). If you'd like to get
started with R and learn how to use it as a statistical
computing package with (mainly) a command line interface,
consider taking Dr. John Verzani's online course
"Introduction to R – Statistical Analysis,” January 14 –
February 11 at statistics.com. (We also offer courses that
take the full "programming language" approach to R; see below.)
Upcoming Courses:
Jan 14: Introduction to R – Statistical Analysis (more below)
Feb 11: Modeling in R
Mar 4: Introduction to R - Data Handling
Apr 15: R Programming
Apr 22: Microarray Analysis in R
Apr 29: R Graphics
"Introduction to R – Statistical Analysis” covers how to use R
to summarize and graph data, calculate confidence intervals,
test hypotheses, assess goodness-of-fit, and perform linear
regression. Prior familiarity with R is not assumed.
John Verzani is a member of the faculty at the College of Staten
Island of the City University of New York, and the author of
"Using R for Introductory Statistics" (CRC Press), on which
this course is based. His research interests and publications
are in the area of superprocesses. Participants can ask
questions and exchange comments with Dr. Verzani via a private
discussion board throughout the period.
Details:
http://www.statistics.com/courses/using-r/Rstatistics/
The course takes place online at statistics.com in a series
of 4 weekly lessons and assignments, and requires about
15 hours/week. Participate at your own convenience; there
are no set times when you are required to be online.
You may leave the list at any time by sending the command
SIGNOFF allstat
to [log in to unmask], leaving the subject line blank.
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