Design of a new Z-test for the uncertainty of Covid-19 events under Neutrosophic statistics

Background The existing Z-test for uncertainty events does not give information about the measure of indeterminacy/uncertainty associated with the test. Methods This paper introduces the Z-test for uncertainty events under neutrosophic statistics. The test statistic of the existing test is modified...

Full description

Saved in:
Bibliographic Details
Published in:BMC medical research methodology Vol. 22; no. 1; pp. 99 - 6
Main Author: Aslam, Muhammad
Format: Journal Article
Language:English
Published: London BioMed Central 06.04.2022
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Classical statistics
Coronaviruses
COVID-19
COVID-19 - diagnosis
Data
Decision making
Epidemics
Evaluation
Fuzzy logic
Health Sciences
Humans
Hypotheses
Information management
Mathematical statistics
Medical research
Medicine
Medicine & Public Health
Methods
Research methodology
Saudi Arabia
Simulation
Statistical Theory and Methods
Statistics
Statistics for Life Sciences
Theory of Medicine/Bioethics
Uncertainty
Z test
Saudi Arabia
Classical statistics
Uncertainty
Data
Simulation
Z test
ISSN:1471-2288, 1471-2288
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background The existing Z-test for uncertainty events does not give information about the measure of indeterminacy/uncertainty associated with the test. Methods This paper introduces the Z-test for uncertainty events under neutrosophic statistics. The test statistic of the existing test is modified under the philosophy of the Neutrosophy. The testing process is introduced and applied to the Covid-19 data. Results Based on the information, the proposed test is interpreted as the probability that there is no reduction in uncertainty of Covid-19 is accepted with a probability of 0.95, committing a type-I error is 0.05 with the measure of an indeterminacy 0.10. Based on the analysis, it is concluded that the proposed test is informative than the existing test. The proposed test is also better than the Z-test for uncertainty under fuzzy-logic as the test using fuzz-logic gives the value of the statistic from 2.20 to 2.42 without any information about the measure of indeterminacy. The test under interval statistic only considers the values within the interval rather than the crisp value. Conclusions From the Covid-19 data analysis, it is found that the proposed Z-test for uncertainty events under the neutrosophic statistics is efficient than the existing tests under classical statistics, fuzzy approach, and interval statistics in terms of information, flexibility, power of the test, and adequacy.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1471-2288
1471-2288
DOI:10.1186/s12874-022-01593-x