• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.19-28
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• 2018

In this paper, we studied on the sampling of ocean meteorological data to analyze signature of naval ships. The newest ocean meteorological data, that was quality controled by the Korea Meteorological Administration(KMA), was collected. Outliers were removed from the data by setting the usable range of data. After that, the data size was reduced through the random sampling method, taking geopolitical significance and effective area of buoy, for probabilistic analysis. Moreover, the sample sizes were set at 100, 200, and 400 by considering the population size and a 95% confidence level. The final sample was obtained using the two-dimensional stratified sampling method based on highly correlated water temperature and air temperature. The sum of the squared errors and the confidence interval was calculated to compare the result of sampling. As a result, this study proposed reasonable sample size for infra­red signature analysis of naval ships.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

• Survey Research
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• v.7 no.2
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• pp.39-52
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• 2006

Most of Korean survey institutions adopt quota sampling for telephone surveys based on region, gender and age-band. In weekdays, it is well blown that there exist substantial differences in day time in-house rate by individual's socio-demographic attributes. So, quota sampling may induce systematic respondent selection bias. To solve the problem, we propose "time-balanced quota sampling" in which interviewer's call time-band is added as an quota variable. Furthermore, we propose "time-balanced quasi-quota sampling" which is derived by partially relaxing evening time quotas in time-balanced quota sampling. We compare the conventional and the newly proposed quota sampling schemes by drawing Monte Carlo samples from the hypothetical population for which the Korea 2004 time use survey data is assumed.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.99-105
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• 1998

본 논문에서는 매우 민감한 조사에서 모집단이 여러 개의 집락으로 구성되어 있을 때, 모집단으로부터 집락을 단순임의추출한 후 추출된 각 집락에서 다시 조사단위의 표본을 추출하는 2단계 집락추출법에 확률화응답모형을 적용하였다. 그리고, 일정한 비용 하에서 분산을 최소로 하는 1단계 집락의 수와 2단계 집락에서 추출된 조사단위의 수의 최적값을 구하여 최소분산의 형태를 도출하였다.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.113-132
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• 2000

본 연구에서 구현하 SLWES(Sampling Learning Web Expert System)은 인터넷 환경에서 표본조사의 학습과 실제 표본조사 자료로부터 모수를 추정할 수 있도록 웹 프로그래밍 기술과 HTML을 결합하여 학습시스템과 통계계산 시스템, 그리고 전문가시스템으로 구성된 표본조사 학습전문가 시스템이다. SLWES는 표본조사에 대하여 전문 지식이 없거나 통계패키지 사용에 익숙하지 않은 비전문가들에게 표본추출법, 무수측정 표본크기 결정 등 표본조사에 대한 이론 학습과 실습의 기회를 인터넷 환경에서 직접 제공함으로써 사용자의 지식에 따라 표본조사론에 대해 체계적이고 효과적으로 학습할 수 있는 시스템이다. 또한 SLWES는 실제 표본조사의 표본추출에 적용될 수 있고 수집된 자료로부터 모수를 추정할수 있으므로 표본조사에 활용될 수 있다.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.477-483
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• 2015

This study deals with the decision problem of sample size by the relative standard error of estimates derived from survey results in successive occasions. The population of the construction in business survey results is used to calculate quartile of the relative standard error of the 1,000 sample obtained from simple or stratified random sampling. The sample size at time t with a relative standard error of the point (t-1) in the successive occasions were calculated according to the sampling method. As a result, in terms of the sample size according to the size of the relative standard error of the (t-1), simple random sampling differs significantly from stratified sampling. In addition, we could see differences in sample size (depending on how the population is stratified) and that careful attention is required in the problem of sample size by the relative standard error of estimates derived from survey results in successive occasions.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1047-1061
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• 2015

Stratified random sampling is a powerful sampling strategy to reduce variance of the estimators by incorporating useful auxiliary information to stratify the population. Sample allocation is the one of the important decisions in selecting a stratified random sample. There are two common methods, the proportional allocation and Neyman allocation if we could assume data collection cost for different observation units equal. Theoretically, Neyman allocation considering the size and standard deviation of each stratum, is known to be more effective than proportional allocation which incorporates only stratum size information. However, if the information on the standard deviation is inaccurate, the performance of Neyman allocation is in doubt. It has been pointed out that Neyman allocation is not suitable for multi-purpose sample survey that requires the estimation of several characteristics. In addition to sampling error, non-response error is another factor to evaluate sampling strategy that affects the statistical precision of the estimator. We propose new sample allocation methods using the available information about stratum response rates at the designing stage to improve stratified random sampling. The proposed methods are efficient when response rates differ considerably among strata. In particular, the method using population sizes and response rates improves the Neyman allocation in multi-purpose sample survey.

• Journal of Korean Society of Forest Science
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• v.17 no.1
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• pp.35-42
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• 1973

Deciduous trees grown naturally in the forest of Korea usually have an irregular Lee-form and their utility has been decreased. In Korea, most of the deciduous stands are distributed in the hinterland. A shortage of the total growing stock made utilization of them necessary in this country even though some difficulties to be cutted and transported are accompanied. Therefore, this study was conducted to select the suitable sampling method for surveying them. The results investigated are as follows. 1. Three locations being 10 hectares in each location for the plots were chosen and surveyed with six $20m{\times}50m$ rectangular sample plots by four types of sampling method below. And the result is shown in Table 1. A. Random sampling by grids B. Random sampling by co-ordinates C. Systematic line plot. D. Sub-sampling 2. One hundred and fifty hectares from all plots were sectioned through the application of aerial photography scaled of 1 : 15,000. The author divided forest types according to diameter class and crown density with mirror stereoscope. The forest types were divided into three classes. Seven sample plots from the area of 150 hectars are systematically arranged and the results investigated on the circular sample point of 0.1 hectare are shown in Table 4. 3. There were no significant differences between results by sampling method and by diameter measurement method (population mean) as shown in Table 3. 4. Random sampling by grid and systematic line plot are better than others. 5. There are more over-estimated values when the circular sample point is used than where the rectangular sample point. 6. As forest stands are irregular, smaller number of sample points will make many errors.

• Survey Research
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• v.10 no.3
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• pp.157-172
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• 2009

For a survey research in which the characteristics of the population of interest are investigated from a sample, representativeness of the sampling frame is one of the most important part to be considered. If the sampling frame fails to represent the population properly, statistical procedures based on the even efficient sampling design result in significant nonsampling biases and thus the statistical validities of the results could be damaged. But the construction of the reliable sampling frame that covers the population properly costs money and time and thus the sampling frame based on a census or a large scale survey is often used in practice. For example, the sampling frame based on the population households census is used for many household surveys in Korea. But due to the time difference between the census and a survey of interest, the sampling frame constructed from the census is expected to fail to cover the population of interest. Especially, one could expect a large amount of population and household movement in a large city like Seoul. Thus in our research, we considered the construction of new sampling frame and the procedure of sample selection for 2008 Seoul survey. We analyzed the sampling frame based on 2005 population households census and found that it does not represent the population properly. Thus, we proposed a new sampling frame based on resident registration DB for 2008 Seoul survey. We also proposed the sampling weights and estimator of the population mean based on the sample selected from the newly constructed sampling frame.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1185-1199
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• 2016

Two phase sampling (double sampling) is often used when there is inadequate population information for proper stratification. Many recent papers have been devoted to the estimation method to improve the precision of the estimator using first phase information. In this study we suggested outlier weight adjustment methods to improve estimation precision based on the weight of the generalized ratio-cum-product estimator. Small simulation studies are conducted to compare the suggested methods and the usual method. Real data analysis is also performed.