BL COLLEGE JOURNAL

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Inclusion Probability in Simple Random Sampling by Hypergeometric Distribution

Author

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

References:

Bebbington, A.C. (1975). A simple method of drawing a sample without replacement. Applied Statistics, 24, 136.

Cochran, W.G. (1977). Sampling Techniques. John Wiley and Sons.

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

Miller, Irwin and Miller, Merylees (1999). John E Freund’s Mathematical Statistics, Prentice Hall, New Jersey, USA.

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

Ting, Daniel (2021). Simple, Optimal algorithms for simple random sampling without replacement. https://arxiv.org/pdf/2104.05091.pdf

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. https://doi.org/10.62106/blc2022v4i2e1

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. https://doi.org/10.62106/blc2022v4i2e1

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