Sampling Inspection Plan to Test Daily COVID-19 Cases Using Gamma Distribution under Indeterminacy Based on Multiple Dependent Scheme

Muhammad Aslam, Gadde Srinivasa Rao and Mohammed Albassam
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Muhammad Aslam: Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
Gadde Srinivasa Rao: Department of Mathematics and Statistics, University of Dodoma, Dodoma P.O. Box 259, Tanzania
Mohammed Albassam: Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia

IJERPH, 2022, vol. 19, issue 9, 1-14

Abstract: The purpose of this paper is to develop a multiple dependent state (MDS) sampling plan based on time-truncated sampling schemes for the daily number of cases of the coronavirus disease COVID-19 using gamma distribution under indeterminacy. The proposed sampling scheme parameters include average sample number (ASN) and accept and reject sample numbers when the indeterminacy parameter is known. In addition to the parameters of the proposed sampling schemes, the resultant tables are provided for different known indeterminacy parametric values. The outcomes resulting from various sampling schemes show that the ASN decreases as indeterminacy values increase. This shows that the indeterminacy parameter plays a vital role for the ASN. A comparative study between the proposed sampling schemes and existing sampling schemes based on indeterminacy is also discussed. The projected sampling scheme is illustrated with the help of the daily number of cases of COVID-19 data. From the results and real example, we conclude that the proposed MDS sampling scheme under indeterminacy requires a smaller sample size compared to the single sampling plan (SSP) and the existing MDS sampling plan.

Keywords: COVID-19 data; multiple dependent state; single sampling plan; classical statistics; indeterminacy; average sample number; time-truncated sampling schemes (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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