Title

An expert system on selection of appropriate nonparametric statistical tests

Date of Publication

1996

Document Type

Master's Thesis

Degree Name

Master in Computer Application

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Information Technology

Thesis Adviser

Arnulfo Azcarraga

Defense Panel Chair

Peter Fernandez

Defense Panel Member

Philip Chan
Kelsey Hartigan Go

Abstract/Summary

The Nonparametric Statistical Expert System (NOSES) is designed to assist users in selecting appropriate nonparametric statistical tests for analyzing data. The system consists of two (2) components. The first component involves utilization of pure raw data provided by users and other information, namely, variable measured by the data, unit of measurement, and the nonparametric statistical problem being addressed. Raw data supplied are processed to generate parameters or characteristics of data, including number of samples, number of observations, sum, and mean. The second component entails the process of recommending appropriate nonparametric statistical test(s) on the basis of the parameters produced and other information supplied by users. The system also provides a description of each nonparametric statistical test included in the study and a glossary of relevant statistical terms.

Abstract Format

html

Format

Print

Accession Number

TG02547

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

46, [131] leaves; 28 cm.

Keywords

Expert systems (Computer science); Nonparametric statistics; Electronic data processing; Artificial intelligence; Statistics -- Computer programs

This document is currently not available here.

Share

COinS