• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.111-120
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• 2001

Either systematic sampling or stratified sampling is usually applied to the business conditions survey when companies don't have much difference in their size. But the cutoff systematic sampling is an efficient method when only a few companies are so large that the total of them almost equals to the total of whole companies. Throughout this paper, three estimators of total and their variance estimations depending on three kinds of sampling schemes are discussed, and are compared with them via their variances. It is proved that the cut-off systematic sampling is most efficient by using a real data of the logging business conditions survey.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.209-222
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• 2013

We apply stratified cluster sampling to a replicated systematic unrelated question model for a large scale survey in which the population is comprised of several strata developed by several clusters and with sensitive parameters. We first present a replicated systematic unrelated question model using an unrelated question model to procure sensitive information from the population of clusters and then develop a suggested model to an unrelated question by a stratified cluster replicated systematic sampling that can be used in large population of strata. We cover the proportional and optimum allocation for the suggested model. Finally, we compare and analyze the efficiency of the suggested model with the replicated systematic unrelated question model.

• Survey Research
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• v.6 no.2
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• pp.1-32
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• 2005

The accuracy of exit poll mainly depends on the sampling method of voting places. For exit poll, we propose a probability sampling method of selecting voting places as an alternative to the bellwether polling place sampling. Through an empirical study based on the 2004 general election data, the efficiency of the suggested systematic sampling from ordered voting places was evaluated in terms of mean prediction error and it turns out that the proposed sampling method outperformed the bellwether polling places sampling. We also calculated the variance of estimator from the proposed sampling, and considered the sample size problem to guarantee the target precision using the design effect of the proposed sample design.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.291-299
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• 2020

The purpose of this study was to propose the most cost-effective sampling method, by analyzing the cost of forest resource investigation per sampling method for the planned harvesting area of in Chunyang-myeon, Byeonghwa-gun, Gyeongsangbuk-do, Korea. For this study, three sampling methods were selected: random sampling method, systematic sampling method, and line transect method. For each method, sample size, hourly wage, number of sample points, survey time, travel time, the sample error rate of the estimated average volume, and the desired sampling error rate were used to calculate the cost of forest resource inventories. Thus, 10 sampling points were extracted for each sampling method, and the factors required for cost analysis were calculated via a field survey. As a result, the field survey cost per ha using the random sampling method was found to be have the lowest cost, regardless of the desired sampling error rate, followed by the systematic sampling method, and the line transect method.

• Survey Research
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• v.10 no.1
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• pp.155-168
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• 2009

As an efficient sampling design, stratified random sampling is often used when auxiliary information is available at the designing stage. Although one - per - stratum design is an efficient design that can be used when many auxiliary variables are available, it does not provide any unbiased variance estimator. With a two - per - stratum sample in which two elements are selected from each stratum, it is possible to obtain an unbiased variance estimator. However the loss of efficiency could be significant if any important stratification variable is missed. In this study, we investigated a sampling design that uses the all given auxiliary information and also permits an unbiased variance estimator suggested by Park and Fuller(2008). Through a simulation study, we compared several stratified random sampling and systematic sampling design. We also applied the proposed stratified sampling designs to 2007 youth panel data.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1033-1041
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• 2013

In this paper, we investigate several variance estimators for pps systematic sampling. Unfortunately, there is no unbiased variance estimators for a systematic sample because systematic sampling can be regarded as a random selection of one cluster. This study provides guidance on which variance estimator may be more appropriate than others in several circumstances. We judge the efficiency of variance estimators for systematic sampling based on of their relative biases and relative mean square error. Also, we investigate variance estimation problems for two-stage systematic sampling applied for the Food Raw Material Consumption Survey and the Establishment Labor Force Survey simulation study, in order to consider the popular two-stage pps systematic sample design for establishment and household survey in Korea.

• Korean Journal of Microbiology
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• v.43 no.3
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• pp.210-216
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• 2007

The principal objective of this study was to analyze 16S rDNA-ARDRA of the humus forest soil via an improved manual method and an ISOIL kit on the basis of the UPGMA clustering of the 16S rDNA combined profile, 44 ARDRA clusters of 76 clones via the ISOIL kit method and 45 ARDRA clusters of 136 clones via the improved manual method. On the basis of the 16S rDNA sequences, 44 clones from the ARDRA clusters by the ISOIL kit were classified into 3 phyla : ${\alpha}-,\;{\beta}-,\;{\gamma}-,\;{\delta}-Proteobacteria$, Acidobacteria and Actinobacteria. Using the improved manual method, the specimens were classified into 6 phyla : the ${\alpha}-,\;{\beta}-,\;{\gamma}-,\;{\delta}-Proteobacteria$, Acidobacteria, Bacteroides, Verrucomicrobia, Planctomycetes and Gemmatomonadetes. As a result, the modified manual method indicated greater phylogenetic diversity than was detected by the ISOIL kit. Approximately 40 percent of the total clones were identified as ${\alpha}-Proteobacteria$ and 30 percent of the total clones were ${\gamma}-Proteobacteria$ and assigned to dominant phylogenetic groups using the ISOIL kit. Using the modified manual method, 41 percent of the total clones were identified as Acidobacteria and 28 percent of total clones were identified as ${\alpha}-proteobacteria$ and assigned to dominant phylogenetic groups.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.11a
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• pp.157-168
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• 2000

In this paper we point out another advantage of systematic sampling over simple random sampling, which have not yet been spelled out in the literature. After a single sample is drawn by a sampling scheme, it is important to check whether the achived sample represents the population well or not. Therefore, a sampling scheme which avoids the possibility of selecting non-preferred samples is desirable. The simulation results are given to illustrate that, in the ordered population, the possibility of selecting non-preferred sample by systematic sampling is lower than that by simple random sampling.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.04a
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• pp.153-165
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• 2001

In this paper we point out another advantage of systematic sampling over simple random sampling, which have not yet been spelled out in the literature. After a single sample is drawn by a sampling scheme, it is important to check whether the achieved sample represents the pupulation well or out. Therefore, a sampling scheme which avoids the possibility of selecting non-preferred samples is desirable. The simulation results are given to illustrate that, in the ordered population, the possibility of selecting non-preferred sample by systematic sampling is lower than that by simple random sampling.

• Survey Research
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• v.2 no.2
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• pp.153-165
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• 2001

In this paper we point out another advantage of systematic sampling over simple random sampling, which have not yet been spelled out in the literature. After a single sample is drawn by a sampling scheme, it is important to check whether the achived sample represents the population well or not. Therefore. a sampling scheme which avoids the possibility of selecting non-preferred samples is desirable. The simulation results are given to illustrate that, in the ordered population, the possibility of selecting non-preferred sample by systematic sampling is lower than that by simple random sampling.