Hi List,
I had the pleasure of taking Dr Bob Muenchen's interview for his upcoming
book R For SAS and SPSS users. He has spent 27 years in this field while I
have spent almost that much on earth.
So this is more like a fan blog interview. I thought it would be of use to
people curious about R, or even SAS , or SPSS if they have not worked on
either of these packages before.
Having fought my own battles for cheaper software, or trying to learn R by
kicking the GUI habit,I found this quite useful
It would of extra interest to people in developing world as they effectively
pay 7 times as much due to economic purchasing parity for softwares, even
though statistical decision making is the area they need the most to
optimize their resources and planning.R is free.
So here goes, and thanks for your time, and apologies if you think this is
spam. Please send the comments (especially the SAS-L list ) individually on
my email.
Ajay
http://www.decisionstats.com/?p=599
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Note-*Dr Robert Muenchen (pronounced Min'-chen) is the author of the famous
R for SAS and SPSS users, and his forthcoming book is an extensive tutorial
on anyone wanting to learn either SAS, SPSS ,or R or even to migrate from
one platform to another.In an exclusive interview to
www.decisionstats.comBob agreed to answer some questions on the book ,
and on students planning
to enter science careers.*
*What made you write the R For SAS and SPSS users?*
*The book-
*
A few years ago, all my colleagues seemed to be suddenly talking about R.
Had I tried it? What did I think? Wasn't it amazing? I searched around for a
review and found an article by Patrick Burns, "R Relative to Statistics
Packages" which is posted on the UCLA site (*
http://www.ats.ucla.edu/stat/technicalreports/*). That article pointed out
the many advantages of R and in it Burns claimed that knowing a standard
statistics package interfered with learning R. That article really got my
interest up. Pat's article was a rejoinder to "Strategically using General
Purpose Statistics Packages: A Look at Stata, SAS and SPSS" by Michael
Mitchell, then the manager of statistical consulting at UCLA (it's at that
same site). In it he said little about R, other than he had "enormous
difficulties" learning it that he had especially found the documentation
lacking.
I dove in and started learning R. It was incredibly hard work, most of which
was caused by my expectations of how I thought it ought to work. I did have
a lot to "unlearn" but once I figured a certain step out, I could see that
explaining it to another SAS or SPSS user would be relatively easy. I
started keeping notes on these differences for myself initially. I finally
posted them on the Internet as the first version of *R for SAS and SPSS
Users*. It was only 80 pages and much of its explanation was in the form of
extensive R program comments. I provided 27 example programs, each done in
SAS, SPSS and R. A person could see how they differed, topic by topic. When
a person ran the sections of the R programs and read all the comments, he or
she would learn how R worked.
A web page counter on that document showed it was getting about 10,000 hits
a month. That translates into about 300 users, paging back and forth through
the document. An editor from Springer emailed me to ask if I could make it a
book. I said it might be 150 pages when I wrote out the prose to replace all
the comments. It turned out to be 480 pages!
http://www.amazon.com/SAS-SPSS-Users-Statistics-Computing/dp/0387094172/ref=pd_bbs_sr_1?ie=UTF8&s=books&qid=1217456813&sr=8-1
You can read the rest of the interview here - www.decisionstats.com (which
is a non commercial non advertising website )
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