[R-sig-finance] Re: [R] How to Describe R to Finance People

[Dirk Eddelbuettel]

Kevin,

This is a nice start. I'll Cc this back to the recently formed 'R in
Finance' list we formed as a result of the two Finance sessions at use useR.

One small correction would be that the number of CRAN packages is now in
excess of 350 (not 150). 

And a point you may want to add is that the S language has been used in some
geek corners of Finance for decades; the proximity of Bell Labs to Wall St
may have something to do with that, as does of course the power and elegance
of the language.

S-Plus also offers some fancypants add-on modules, and we'll try hard over
the next few months and years to catch up. A major help in that regard is
Diethelm Wuertz' most excellent Rmetrics collection at

	http://www.rmetrics.org

This is currently windows-only, but Diethelm and I are committed to getting
it into Debian (and my Quantian) so that general Unix/Linux use should fall
out as a side benefit.

Hope this helps, Dirk

On Fri, Jun 04, 2004 at 11:50:32PM +1200, Ko-Kang Kevin Wang wrote:
> Hi,
> 
> I've been doing a joint research with someone from the Property
> Department here and she is about to give a presentation on the
> results.  The audience will include people from Property and Finance,
> and she is wondering how to describe R to these people (as I used R to
> do the analyses), since she has never even heard of R before our joint
> research (and has been using SPSS).  The difficult part is she has
> only about 1 ~ 2 minutes to talk about R.
> 
> The following is what I have in mind, any suggestions from people in
> Finance will be greatly appreciated!  (From our research together I
> think it may be safe to assume the audience will know, or at least
> have heard of, basic statistical terminology such as multiple linear
> regression and dummy variables).
> 
> \begin{quote}
> R was originally developed by Dr. Ross Ihaka and Dr. Robert Gentleman
> from the Department of Statistics at the University of Auckland in
> 1992.  It is free and in the last decade it has evolved into one of
> the most powerful statistical software, with over 150 user-contributed
> add-on packages.  It is not only used by statisticians or scientists,
> but also econometricians and people in finance due to its cost (FREE)
> and its powerfulness.
> 
> Although it has a slightly higher learning curve than SPSS-like
> program, it gets easier to use once one is familiar with it.  One of
> the main advantage it has over SPSS-like software is that you do not
> need to explicitly create dummy variables.  You only need to specify
> your dependent variable and independent variables and R will fit it
> (and create dummy variables automatically) for you.
> 
> It also has many state-of-art free resources, including manuals,
> contributed tutorials and documentations, online.  A free mailing list
> is also available for people to ask questions and questions are
> usually answered by more experienced users around the world within a
> few hours (sometimes even within minutes).
> \end{quote}
> 
> As mentioned above, she was rather impressed when I mention that one
> does not need to create dummy variables in R.  Therefore I am thinking
> she might be interested in mentioning it in her talk.
> 
> I have never had experience of trying to introduce R to
> non-Scientists, hence I would appreciate any comments!
> 
> Cheers,
> 
> Kevin
> 
> --------------------------------------------
> Ko-Kang Kevin Wang, MSc(Hon)
> SLC Stats Workshops Co-ordinator
> The University of Auckland
> New Zealand
> 
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