Top-down statistical estimation on a database
By: [by] Neil C. Rowe
Contributors: Naval Postgraduate School (U.S.)
Publisher: Naval Postgraduate School
Published: 1984
Place of publication: Monterey, California
Language: eng
Number of pages: 20
Subjects: Mathematical analysis; Software engineering; Artificial intelligence; Databases
Description: The size of data sets subjected to statistical analysis is increasing as computer technology develops. Quick estimates of statistics rather than exact values are becoming increasingly important to analysts. The author proposes a new technique for estimating statistics on a database, a top-down alternative to the bottom-up method of sampling. This approach precomputes a set of general-purpose statistics on the database, a database abstract, and then uses a large set of inference rules to make bounded estimates of other, arbitrary statistics requested by users. The inference rules form a new example of an artificial-intelligence expert system. There are several important advantages of this approach over sampling methods. (Author)
Notes: Title from cover.

"Prepared for: Chief of Naval Research"--Cover.

"January 1984"--Cover.

"NPS52-84-001"--Cover.

DTIC Identifiers: Expert systems, PE61152N.

Author(s) key words: Databases, statistics, counts, means, exploratory data analysis, sampling, artificial intelligence, expert systems, production systems, interval mathematics, estimation, database query languages, data abstraction, rule-based systems.

Includes bibliographical references (p. 18-19).

"Approved for public release; distribution unlimited"--Cover.

Technical report; 1984.

aq/aq cc:9116 06/04/99.

kmc/kmc 10/27/09.