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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:BMC medical research methodology Ročník 22; číslo 1; s. 99 - 6
Hlavní autor: Aslam, Muhammad
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 06.04.2022
BioMed Central Ltd
Springer Nature B.V
BMC
Témata:
ISSN:1471-2288, 1471-2288
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie: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