[R] R routines vs. MATLAB/SPSS Routines
gunter.berton at gene.com
Fri Oct 26 18:38:56 CEST 2007
By "routines" I assume that you mean "underlying numerical algorithms."
Two part answer:
1) R has a lot more of them than SPSS, and more in most data analytical
related areas than Matlab (but Matlab is the right tool for, say,
differential equation solving).
2) A detailed answer to the question is highly technical, requiring a heavy
numerical analysis background to discuss intelligently. Since most students
(indeed, non-specialists like myself, included) will not have this
background, the short answer is: "this is beyond the scope of your ability
As a general comment, core R algorithms are probably among the best in the
business (because R's core developers are a pretty outstanding bunch of
folks and have done extensive testing); but beyond that, caveat emptor!
Genentech Nonclinical Statistics
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of Frank Thomas
Sent: Friday, October 26, 2007 8:54 AM
To: r-help at r-project.org
Cc: matt.dubins at utoronto.ca
Subject: Re: [R] R routines vs. MATLAB/SPSS Routines
Some major differences between R and SPSS:
1/ The learning curve of R is steep and the one of SPSS is largely flat.
A difference any student will rapidly understand.
2/ The user interface in R is underdeveloped, in comparison to SPSS.
3/ In R without loving to spend time in programming you get nothing.
With SPSS your students will concentrate on content, not on technology.
4/ SPSS is so easy to use that the statistical conditions for using
specific procedures get easily forgotten. R is more close to the
programming side so no way to forget the foundations.
5/ The economic price of SPSS is really steep, you pay more than 30
years of development. R is free, but the real price for a student is his
or her time to learn, which can also be steep.
I think, how to evaluate the differences is in part a question of the
mindset and the work environment of the future user. If your students
are more mathematicians, program developers, engineers, science people,
etc. and need to tweak a procedure to single case applications you will
have an easy public with R. If they are more of economic, social
sciences, service industry people, and routine applications or large
data sets will be their job SPSS, SAS, SPAD are more adapted.
But this may be ground for discussion.
BTW: Contrary to some ideas both R & SPSS can be programmed and the
algorithms for both have been published. So, no matter whether open
source or private property you know what you do (if you want).
Hope this helps,
Matthew Dubins wrote:
> Hi all,
> I've become quite enamored of R lately, and have decided to try to teach
> some of its basics (reading in data, manipulation and classical stats
> analyses) to my fellow grad students at the University of Toronto. I
> sent out a mass email and have already received some positive
> responses. One student, however, wanted to know what differentiates the
> routines that R uses, from those that MATLAB and SPSS use. In other
> words, in what respects do R routines work faster/more efficiently/more
> accurately than those of MATLAB/SPSS.
> I thank you in advance for any answer you can give me (or rather, the
> inquiring student).
> Matthew Dubins
> R-help at r-project.org mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reroducible code.
Dr. Frank Thomas
FTR Internet Research
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