Jacques Basaldúa wrote:
Hello,
Just an explanation on something I may have explained badly. I see we
agree in the fundamental.
Correcting bias in that estimate should lead to better sampling.
This is usually called "continuity correction"
http://en.wikipedia.org/wiki/Continuity_correction. The estimator
is not really biased, but because it is a quotient of integers it
requires a continuity correction specially when the integers are small
or zero is involved. That is included in the intervals I suggested.
That's about how to fit a continuous curve to a discrete one. It's
really just an approximation that increases as the sample size gets
better. The article mentions that both np and n(1-p) must exceed 5 for
most to consider the approximation to even be valid. The analysis I
gave has no restrictions on the sample size (it even works for a sample
size of zero)
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