Re: [R] A comment about R:

From: Kort, Eric <Eric.Kort_at_vai.org>
Date: Wed 04 Jan 2006 - 05:37:42 EST

Berton Gunter writes....
> Ummmm....
>
> I cannot say how easy or hard R is to learn, but in response to the
UCLA
> commentary:
>
> > 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.
>
> Please note: the first sentence of the Preface of THE Green Book
> (PROGRAMMING WITH DATA: A GUIDE TO THE S LANGUAGE) by John Chambers,
the
> inventor of the S Language, explicitly states:
>
> "S is a programming language and environment for all kinds of
computing
> involving data."
>
> I think this says that R is **not** meant to be a statistical package
in
> the
> conventional sense and should not be considered one. As computing
> involving
> data is a complex and frequently messy business on both technical
> (statistics), practical (messy data), and aesthetic (graphics, tables)
> levels, it is perhaps to be expected that "a programming language and
> environment for all kinds of computing involving data" is complex.
> Personally, I find that (Chambers's next sentence) R's ability "To
turn
> ideas into software, quickly and faithfully," to be a boon. <snip>

Right.

So in 2 months I will finish my MD program here in the U.S. I also have a master's degree in Epidemiology (in which we used SAS)--but that hardly qualifies me as statistics expert. Nonetheless, I have learned to use R out of necessity without undue difficulty. So have multiple of my colleagues around me with MDs, PhDs, and Master's degrees. We do mainly microarray analysis, so the availability of a rapidly developing and customizable toolset (BioC packages) is essential to our work.

And, in the same vein of others' comments, R's "nuts and bolts" characteristics make me think, learn, and improve. And the fear of getting Ripleyed on the mailing list also makes me think, read, and improve before submitting half baked questions to the list.

So in sum, I use R because it encourages thoughtful analysis, it is flexible and extensible, and it is free. I feel that these are strengths of the environment, not weaknesses. So if an individual finds another tool better suited for their work that is obviously just fine, but I hardly think these characteristics of R are grounds for criticism, excellent proposals for evolution of documentation and mailing lists notwithstanding.

-Eric
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