For general points, you can look at "An Introduction to the S Language" in the tutorials section of the Burns Statistics website.
For your specific audience, it sounds like property is of special consideration
so you could come up with an example of how R can easily
analyse spatial relationships (graphically or analytically) that would be
virtually impossible without it.
My viewpoint on the issue of cost is that it is the free as in "libre" that is
the most important part in finance. Once R breaks through the gate
once, it is free to spread. Often the bureaucratic cost of buying something
is a much larger impediment than the dollar cost.
Patrick Burns
Burns Statistics [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and "A Guide for the Unwilling S User")
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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