On 07/01/2010 03:29 AM, Dr. David Kirkby wrote:
On 03/ 1/10 12:23 AM, Sharpie wrote:
John Maindonald wrote:
I came across this notice of an upcoming webinar. The issues identified
in the
first paragraph below seem to me exactly those that the R project is
designed
to address. The claim that "most research software is barely fit for
purpose
compared to equivalent systems in the commercial world" seems to me not
quite accurate! Comments!
It can be argued that this is a reporting bias. Whenever I inform people
doing epidemiology with Excel about Ian Buchan's paper on Excel errors:
http://www.nwpho.org.uk/sadb/Poisson%20CI%20in%20spreadsheets.pdf
there is a sort of reflexive disbelief, as though something as widely
used as Excel could not possibly be wrong. That is to say, most people
using commercial software, especially the sort that allows them to
follow a cookbook method and get an acceptable (to supervisors, journal
editors and paymasters) result simply accept it without question.
The counterweight to the carefree programming style employed by many
researchers (I include myself) is the multitude of enquiring eyes that
find our mistakes, and foster a continual refinement of our programs. I
just received one this evening, about yet another thing that I had never
considered, perfect agreement by rating methods in a large trial. Thus
humanity bootstraps upward. My AUD0.02
Jim
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