🚀 go-pugleaf

Bootstrapping refers to a methodology in which error estimates are
produced by resampling with replacement from a finite set of data,
in order to produce unbiased or less biased estimates of standard
errors. This may be a simplistic defintion that can be improved
upon by the more mathematically oriented, but it's the jist of it.

The reason that n-1 is used in the denominator when calculating
standard deviations of samples is that the squared standard deviation,
the variance, is estimated in an unbiased manner by using n-1 instead
of n. You've estimated a parameter (the mean) in calcuating the sum
of squared deviations about the mean, so you have one less degree of
freedom than when you started. Incidentally, either divisor produces
a biased estimate of the population standard deviation.
--
 David Nichols           Statistical Support Specialist            SPSS, Inc.
 Phone: (312) 329-3684     Internet: nichols@spss.com     Fax: (312) 329-3657
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 Any correlation between my views and those of SPSS is strictly due to chance.