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Determining optimum strata boundaries and sample sizes for skewed population using log-normal distribution

Khan, Mohammad G.M. and Rao, Dinesh K. and Ansari, A.H. and Ahsan, M.J. (2014) Determining optimum strata boundaries and sample sizes for skewed population using log-normal distribution. Communications in Statistics: Simulation and Computation, 44 (5). pp. 1364-1387. ISSN 0361-0918

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The method of choosing the best boundaries that make strata internally homogeneous as far as possible is known as optimum stratification. To achieve this, the strata should be constructed in such a way that the strata variances for the characteristic under study be as small as possible. If the frequency distribution of the study variable x is known, the Optimum Strata Boundaries (OSB) could be obtained by cutting the range of the distribution at suitable points. If the frequency distribution of x in unknown, it may be approximated from the past experience or some prior knowledge obtained at a recent study. Many skewed populations have Log-normal frequency distribution or may be assumed to follow approximately Log-normal frequency distribution. In this paper, the problem of finding the OSB and the optimum sample sizes within the stratum for a skewed population with Log-normal distribution is studied. The problem of determining the OSB is redefined as the problem of determining Optimum Strata Widths (OSW) and is formulated as a Nonlinear Programming Problem (NLPP) that seeks minimization of the variance of the estimated population mean under Neyman allocation subject to the constraint that the sum of the widths of all the strata is equal to the range of the distribution. The formulated NLPP turns out to be a multistage decision problem that can be solved by dynamic programming technique. A numerical example is presented to illustrate the application and computational details of the proposed method. A comparison study is conducted to investigate the efficiency of the proposed method with other stratification methods viz Dalenius and Hodges’ cum method, Geometric method by Gunning and Horgan and Lavallee-Hidiroglou method using Kozak’s algorithm available in the literature. The study reveals that the proposed technique is efficient in minimizing the variance of the estimate of the population mean and is useful to obtain OSB for a skewed population with Log-normal frequency distribution.

Item Type: Journal Article
Additional Information: Online Journal Publication
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User: Generic Account
Date Deposited: 08 May 2014 23:14
Last Modified: 15 Mar 2017 21:52

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