[R] A comment about R:
Ben Fairbank
BEN at SSANET.COM
Tue Jan 3 18:42:31 CET 2006
One implicit point in Kjetil's message is the difficulty of learning
enough of R to make its use a natural and desired "first choice
alternative," which I see as the point at which real progress and
learning commence with any new language. I agree that the long learning
curve is a serious problem, and in the past I have discussed, off list,
with one of the very senior contributors to this list the possibility of
splitting the list into sections for newcomers and for advanced users.
He gave some very cogent reasons for not splitting, such as the
possibility of newcomers' getting bad advice from others only slightly
more advanced than themselves. And yet I suspect that a newcomers'
section would encourage the kind of mutually helpful collegiality among
newcomers that now characterizes the exchanges of the more experienced
users on this list. I know that I have occasionally been reluctant to
post issues that seem too elementary or trivial to vex the others on the
list with and so have stumbled around for an hour or so seeking the
solution to a simple problem. Had I the counsel of others similarly
situated progress might have been far faster. Have other newcomers or
occasional users had the same experience?
Is it time to reconsider splitting this list into two sections?
Certainly the volume of traffic could justify it.
Ben Fairbank
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Kjetil Halvorsen
Sent: Sunday, January 01, 2006 8:37 AM
To: R-help at stat.math.ethz.ch
Subject: [R] A comment about R:
Readers of this list might be interested in the following commenta about
R.
In a recent report, by Michael N. Mitchell
http://www.ats.ucla.edu/stat/technicalreports/
says about R:
"Perhaps the most notable exception to this discussion is R, a language
for statistical computing and graphics. R is free to download under the
terms of the GNU General Public License (see http://www.r-project.
org/). Our web site has resources on R and I have tried, sometimes in
great earnest, to learn and understand R. I have learned and used a
number of statistical packages (well over 10) and a number of
programming languages (over 5), and I regret to say that I have had
enormous diffculties learning and using R. I know that R has a great fan
base composed of skilled and excellent statisticians, and that includes
many people from the UCLA statistics department. However, I feel like R
is not so much of a statistical package as much as it is a statistical
programming environment that has many new and cutting edge features. For
me learning R has been very diffcult and I have had a very hard time
finding answers to many questions about using it. Since the R community
tends to be composed of experts deeply enmeshed in R, I often felt that
I was missing half of the pieces of the puzzle when reading information
about the use of R { it often feels like there is an assumption that
readers are also experts in R. I often found the documentation for R
quite sparse and many essential terms or constructs were used but not
defined or cross-referenced. While there are mailing lists regarding R
where people can ask questions, there is no offcial "technical support".
Because R is free and is based on the contributions of the R community,
it is extremely extensible and programmable and I have been told that it
has many cutting edge features, some not available anywhere else.
Although R is free, it may be more costly in terms of your time to
learn, use, and obtain support for it. My feeling is that R is much more
suited to the sort of statistician who is oriented towards working very
deeply with it. I think R is the kind of package that you really need to
become immersed in (like a foreign language) and then need to use on a
regular basis. I think that it is much more diffcult to use it casually
as compared to SAS, Stata or SPSS. But by devoting time and effort to it
would give you access to a programming environment where you can write R
programs and collaborate with others who are also using R. Those who are
able to access its power, even at an applied level, would be able to
access tools that may not be found in other packages, but this might
come with a serious investment of time to suffciently use R and maintain
your skills with R."
Kjetil
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