An expert system on selection of appropriate nonparametric statistical tests

• Main Author: Sipin, Grace C.
• Format: text
• Published: Animo Repository 1996
• Subjects: Expert systems (Computer science); Nonparametric statistics; Electronic data processing; Artificial intelligence; Statistics > Computer programs; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/1758
• Institution: De La Salle University

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.