Accession Number:

ADA250614

Title:

Epistemological Relevance and Statistical Knowledge

Descriptive Note:

Corporate Author:

ROCHESTER UNIV NY DEPT OF PHILOSOPHY

Personal Author(s):

Report Date:

1989-01-01

Pagination or Media Count:

15.0

Abstract:

For many years, at least since McCarthy and Hayes 1969, writers have lamented, and attempted to compensate for, the alleged fact that we often do not have adequate statistical knowledge for governing the uncertainty of belief, for making uncertain inferences, and the like. It is hardly ever spelled out what adequate statistical knowledge would be, if we had it, and how adequate statistical knowledge could be used to control and regulate epistemic uncertainty. Our purpose here is not to evaluate alternative treatments of uncertainty, but rather to explore the question of how far you can go on the basis of statistical knowledge that you do have, and what considerations must be taken account of in this attempt. Relatively few people have explored the question of how far you can go using statistical knowledge. Artificial Intelligence, Data Fusion Epistemological Relevance, Statistical Knowledge.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE