[R] Another NEWBIE

[Charles and Kimberly Maner]

Hi Frank.  I am (somewhat) new to R as well, but almost a 10 yr SAS veteran.
I work for a very large US Bank and have spent a considerable part of my
career in Corp Mktg leveraging data for, arguably, data mining, next
purchase, attrition, balance diminishment and the like.  I am now managing
an Operations Research group in their Customer Service and Support (aka
Telephone/Call Center Support) within the forecasting and analytics group.
What I have found, broadly and personally, regarding R vs. sAS is the
following:

1.  You simply can't beat the price of R vs. Insightful Corp.'s S-Splus, not
to mention SAS.
2.  The support folks for R are among the very best, (e.g., most helpful,
energetic and enthusiastic to help)
3.  R is far, far leaner from what I have seen thus far for modeling,
binning/discretizing, graphing, etc. vs. SAS.
4.  SAS is, per a previous post, (quite debatably) superior for manipulation
and handling of fantastically large datasets.  I have found that R's
strength is not really in merging datasets and dataset manipulation.
Although, major caveat here, it greatly depends on what you need done to the
data.  For lagging, diffing, binning, R is superior.  For match merging, at
this stage, I vote for SAS.  (Again, I stress I've only 6-8 mos of moderate
R experience.)
5.  The challenge with R is, perhaps, it's very strength--language density.
Once I learn how to do something in R vs. SAS, R's code is fractionally as
large as SAS.  Literally, it may take 10 lines of code in SAS vs. a one
liner in R.  That's powerful.  However, due to my SAS experience, I've
banged out the SAS code and am still looking/hunting for the R equivalent.
However, once doing so, it's, borrowing from a popular vegetable drink
slogan, "Wow, I could have done that in R."
6.  And, lastly, while R is well documented, I seem to find one of the areas
of documentation somewhat lacking is a great big R "recipe" book.
(Suggestions, BTW, are welcome here.)  Documentation of the R language is in
place with more being published, (alongside S-Plus), annually.  However,
there does not appear to be, for example, an "R Transition Recipes for
Experienced SAS Users" book.  That, ultimately, is what would help me, (I
think.)  Again, the issue really is simply learning and using the language.
Experienced R users, I'm convinced, could do everything R I'm doing in SAS,
(with money left over for a few coffees at Starbuck's).

In conclusion, I still think that, given one's budget and projects, there's
a place for SAS and R to co-exist.  But, that paradigm diminishes as (1) the
size of the datasets become smaller and, (2) your problems are more
academic/researchy/specific in nature.  For graphing, esp. w/the Lattice
package, R is simply superior (IMHO), period, to SAS.  (For some reason, SAS
has just not felt the need to improve their graphics, at least the SAS/Graph
part of their offering.)  And, for the SAS lovers out there, this opinion is
mine only as I continue to be primarily a SAS client attempting to
transition to R.

Frank, while I've probably been too wordy, I've attempted to provide another
perspective for you.  Good luck.


Thanks,
Charles


------------------------------

Message: 7
Date: Sat, 19 Jun 2004 18:15:19 +0200 (MEST)
From: "F.Kalder" <Kalderf at gmx.de>
Subject: Re: [R] Another NEWBIE
To: r-help at stat.math.ethz.ch
Message-ID: <6411.1087661719 at www45.gmx.net>
Content-Type: text/plain; charset="us-ascii"

Hi,

Thank you all who anwered me. 

I think, I mainly thought to understand the difference between SPSS /SAS and
R, but didn't really get the point (what explains the question, wich metods
R can't do). Maybe, because I don't have much experience with programming
(near to none). My background in stats goes also only back to indroductory
classes and an advanced course in multivariate statistics. To this, I'm
working with Hair, Anderson, Tatham & Blacks's "Multivariate Data Analysis"
(5th Ed.) as my ressource, mainly with questionnaire analysis (Reliability
Analysis and Factor Analysis, also MDS, Conjoint etc. plus sometimes
standard MANOVA, Multiplke Regression etc.). So, maybe my stats aren't
sophisticated enough to use R, I'm just a standard user of applied
statistical methods, not an academic researcher or even a statistician. It
was mainly a descision by costs, because R is free software. 
With the concept, I completely mistook the R concept as a programming
environment more as a kind of advanced SPSS Syntax (because I also would
call it "programming" when using it), which I now know, is completely wrong.

So, I again thank for your help.


Cheers, Frank.

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