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Inclusion Probability in Simple Random Sampling by Hypergeometric Distribution


Anwar H. Joarder, Department of Computer Science & Engineering, Faculty of Science & Engineering, Northern University of Business and Technology, Khulna-9100, Bangladesh and

A.M. Mujahidul Islam, Upazila Statistical Office, Bangladesh Bureau of Statistics, Dighalia, Khulna-9220, Bangladesh

We review important probability issues in sampling from simple random sampling without replacement. The inclusion probability can be calculated by enumerating samples which is formidable for most cases of large samples or large population. A good number of possible situations have been considered. We prove that hypergeometric mass function provides an elegant solution to the problem.

Keywords: Simple Random Sampling, Inclusion Probability, Hypergeometric Distribution, Conditional Probability


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McLeaod, A.I. and Bellhouse, David R. (1983). A convenient algorithm for drawing a simple random sample. Applied Statistics, 32(2), 182-184.

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Tille, Yves (2006). Sampling Algorithms. Springer.

Ting, Daniel (2021). Simple, Optimal algorithms for simple random sampling without replacement.

How to Cite

MLA 9th Edition

Joarder, Anwar H., and A. M. Mujahidul Islam. “Inclusion Probability in Simple Random Sampling by Hypergeometric Distribution.” BL COLLEGE JOURNAL, vol. 4, no. 2, Dec. 2022, pp. 79–89.

APA 7th Edition

Joarder, A. H., & Islam, A. M. M. (2022). Inclusion Probability in Simple Random Sampling by Hypergeometric Distribution. BL COLLEGE JOURNAL4(2), 79–89.


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