John Tukey differentiates "data analysis" and "statistics." The former may
or may not employ probability while the latter is based upon probability.
Resampling techniques use "empirical probability." In the Fisherian sense,
probability is based upon infinite hypothetical distributions. But for
Rechenbach and von Mises, probability is empirically based on limited
cases that generate relative frequency.
It seems to me that resampling is qualified as a probabilistic model
in Rechenbach and von Mises' view, but not in the Fisherian tradition. My
question is: Should resampling be counted as a probabilistic model?
What is the nature of inference resulted from bootstrapping? Is it a
probabilistic inference?
As I recall, Philip Good said that permutuation tests are still subject
to the Behrens-Fisher problem (unknown population variance). If
resampling is based on empirical probability within the reference set, then
why do we care about the population variance?
Any help will be greatly appreciated.
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Chong-ho (Alex) Yu, Ph.D., MCSE, CNE
Academic Research Professional/Manager
Educational Data Communication, Assessment, Research and Evaluation
Farmer 418
Arizona State University
Tempe AZ 85287-0611
Email: [EMAIL PROTECTED]
URL:http://seamonkey.ed.asu.edu/~alex/
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