In any situation of this sort, the amount of data you
need is related to the amount of variation you expect
to find in the data... and is also related to "how close
do you want your answer to be to the truth" and also
with what probablity do you want to be that close to the
truth. By truth I mean "true average response" or the
population average. Statistical sampling theory is usually
founded on taking a small sample from a large (infinite)
population so that the sample does not "disturb" the
population. If the sample size is a significant fraction
of the entire population (as it will be in this instance,
with only 20 people in the population), then a correction
is needed to the usual formula for determining the correct
sample size. I don't have that formula/correction at
hand, but if you want it (or want a little paper I wrote
on this) let me know at [EMAIL PROTECTED] If you
want the paper, I'll need a fax number to send it to...
it is not digitized. If the response you are measuring
is a "pass/fail" response, that makes life easier because
we can estimate the standard deviation quickly and
painlessly. When all is said and done, with a population
of only 20, the sample will need to be a large fraction of
the population. Perhaps as many as 10 or 12.
Charlie H.
In article 86536f$j77$[EMAIL PROTECTED],
[EMAIL PROTECTED] wrote:
We are going to do a quality system audit (like ISO 9000). How do I
choose the sample size for a particular group of people? Let's say
that there are 20 supervisors and I will audit their knowledge of SPC,
how many should I choose for the audit?
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