Well, we wouldn't try to analyze apples and autos in the same data set. :-)
On the other hand, the similarity is sort of like what one requires for an
efficient tabular data base. Whatever the sample space of events is, it
should consist of events that we can think about together comfortably. If it
takes a paragraph to describe each event, statistical methods aren't likely
to be useful. We need to be able to code the data into compact data sets
like measurements on a sample of objects, or a series of measurements on a
single object. Sorry, I don't know of any formal criteria. Usually this is
only discussed when somebody violates some statistician's common sense. Then
it may be discussed in a rather combative atmosphere but privately, rather
than publicly.
Muriel Strand wrote:
i gather that a collection of events which is analyzed with statistics
must have sufficient similarity (between each event) for the analysis to
be accurate/precise. how similar is sufficient? can anyone recommend
refs (preferably books) that discuss this issue, and provide guidelines
for assuring sufficient similarity? does this consideration affect the
appropriate choice of model?
thanks in advance for sharing your wisdom experience.
--
Any resemblance of any of the above opinions to anybody's official
position is completely coincidental.
Muriel Strand, P.E.
Air Resources Engineer
CA Air Resources Board
2020 L Street
Sacramento, CA 59814
916-324-9661
916-327-8524 (fax)
www.arb.ca.gov
