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...
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| Vydáno v: | BMC medical research methodology Ročník 22; číslo 1; s. 99 - 6 |
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| Hlavní autor: | |
| 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 |
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| 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. |
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| 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 |