NONPARAMETRIC STATISTICAL HYPOTHESIS TESTING IN SOFT SET THEORY

Theories of uncertainty plays a vital role in decision making. Efforts are being made in combining statistical hypothesis testing methods with uncertainty theories having membership and nonmembership values. Soft set theory was developed as a generalization of fuzzy set theory to avoid having diffic...

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Bibliographic Details
Published inTWMS journal of applied and engineering mathematics Vol. 15; no. 3; p. 501
Main Authors Parvathy, C.R, Sofia, A
Format Journal Article
LanguageEnglish
Published Turkic World Mathematical Society 01.03.2025
Subjects
Analysis
Community health services
Decision-making
Monte Carlo method
India
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ISSN2146-1147

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Summary:Theories of uncertainty plays a vital role in decision making. Efforts are being made in combining statistical hypothesis testing methods with uncertainty theories having membership and nonmembership values. Soft set theory was developed as a generalization of fuzzy set theory to avoid having difficulties in assigning membership values. In this paper, an attempt is made to impose statistical hypothesis testing methods in soft set theory to handle decision making problems with linguistic data. For this purpose, non-normality of the data has been analyzed by using Shapiro Wilk test for normality following which Skillings Mack nonparametric test has been computed in soft data using chi-squared distribution and Monte Carlo method. To demonstrate this, significance difference in the sample data set of manpower positions (Radiographers, pharmacists, lab technician, nurses and specialty doctors) in the community health centers in Southern states of India from 2019 to 2022 has been computed. Tools used: R Keywords: Soft set, decision making, hypothesis testing, Skillings Mack test, Shapiro Wilk test. AMS Subject Classification: 62G10, 62D10, 62-04
ISSN:2146-1147