"developerWorks has published several recent articles on the
expanding role of open source software in scientific and
engineering work... One of the recurring points scientists made in
the interviews for those articles is that they're assessing
adoption of open source applications that are worthy competitors to
their commercial counterparts, in the dimensions that matter: the
programs have nearly all the capabilities of proprietary products,
and occasionally more.
"R is just such a program. And although it came up often during
that earlier cycle of profiles, I found then that I had to exclude
it from those stories, simply to limit the articles to manageable
sizes. Several researchers have since emphasized to me that, while
R might be statistical rather than scientific in some pedantic
sense, it's so important that it deserves prompt attention. Let's
take a look, then, at R and related software, with a view to
discussing what R means for the server-side developers and
administrators who read this column..."
"Although acronyms come and go according to the fortunes of
consultancies that coin them, the algorithms and statistical
methods that underlie their success are unchanging. One often comes
across the same old algorithms dressed in new marketing-speak. This
is because a marketing department is unlikely to be excited by the
phrase "maximisation of expected utility", but would thrill at the
prospect of re-branding this statistical workhorse as a "Customer
Delight Engine". This short series of articles will show how a
statistical package called R, distributed under the GNU General
Public licence at no charge, can be used as the analytical engine
for many different Business Intelligence applications.
"R has been designed to allow people to interactively explore
data in search of patterns that are not immediately obvious, and is
therefore an excellent data mining tool. To stretch the mining
analogy further, once an interesting data nugget has been found, a
solid, and mathematically well-founded, statistical procedure is
required to refine the ore. When tested for statistical
significance many data nuggets turn out to be fool's gold. Unlike
some commercial applications, R is capable of going beyond the
exploratory stage and can be used as a touchstone for assessing the
predictive value of data..."
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