• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.13-18
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• 2002

본 논문에서는 급변하는 농촌의 환경을 충분히 반영할 수 있도록 1997년도에 설계되어 사용되고 있는 현행의 농가경제조사를 개선하였다. 새로운 표본 조사구를 선정하기 위하여 1999년도와 2000년도 농가경제조사 조사데이터와 2000년에 실시된 농어업총조사 결과를 심도 있게 분석하였다. 이를 기초로 현재의 농촌 실정에 적합한 조사모집단을 새롭게 구성하였고, 현재의 농촌 환경을 반영할 수 있는 층화 기준을 마련하여 표본 조사구를 추출하였다. 또한, 논벼를 비롯한 6개 주요작물들에 대한 농산물생산비조사의 정도(精度) 향상을 위해서 각 작물별 주산지를 표본 조사구로 선정하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.33-40
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• 2010

In this paper, we consider three macroscopic traffic flow monitoring indices, Travel Time Index(TTI), Acceleration Noise(AN) and Two Fluid(TF) and investigate how to determine a proper rate of probe cars for producing reliable values of these indices. For the analysis, we use classical sampling theories and provide numbers of probe rates using simulation data.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.587-597
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• 2018

Procedures, such as sampling technique, survey method, and questionnaire preparation, are required in order to obtain sample data in accordance with the purpose of a survey. An important procedure is the decision of the sample size formula. The sample size formula is determined by setting the target error and total cost according to the sampling method. In this paper, we propose a sample size formula using population changes over time, estimation error of the previous time and response rate of past data when the target error and the expected response rate are given in the simple random sampling. In actual research, we use estimators that apply complex weights in addition to design-based weights. Therefore, we induce a sample size formula for estimators using design-based weights and nonresponse adjustment coefficients, that can be a formula that reflects differences in response rates when survey methods are changed over time. In addition, we use simulations to compare the proposed formula with the existing sample size formula.

• 전기의세계
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• v.36 no.11
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• pp.796-804
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• 1987

본고에서는 가설검정관련의 표본추출에 관한 기초이론을 체계적으로 정리하고 가설검정기법에 의한 불량정보검출법의 원리를 소개하였다.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.301-309
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• 2017

It is often possible to test for differences in population means when two or more samples are extracted from each N population. However, it is not possible to test for the mean difference if one sample is extracted from each population since a sample mean does not exist. But, by dividing a group of samples extracted one by one into two groups and generating a sample mean, we can identify a heterogeneity that may exist within the group by comparing the differences of the groups' mean. Therefore, we propose a minimum combination t-test method that can test the mean difference by the number of combinations that can be divided into two groups. In this paper, we proposed a method to test differences between means to check heterogeneity in a group of extracted samples. We verified the performance of the method by simulation study and obtained the results through real data analysis.

• The Journal of Korean Society for Radiation Therapy
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• v.23 no.2
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• pp.97-102
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• 2011

Purpose: IMRT QA using 2Dimensional array detector is carried out with condition for discrete dose distribution clinically. And it can affect uncertainty of evaluation using gamma method. We analyze gamma index variation according to grid size and suggest validate range of grid size for IMRT QA in Hospital. Materials and Methods: We performed QA using OniPro I'mRT system software version 1.7b on 10 patients (head and neck) for IMRT. The reference dose plane (grid size, 0.1 cm; location, [0, 0, 0]) from RTP was compared with the dose plane that has different grid size (0.1 cm, 0.5 cm, 1.0 cm, 2.0 cm, 4.0 cm) and different location (along Y-axis 0 cm, 0.2 cm, 0.5 cm, 1.0 cm). The gamma index variation was evaluated by observing the level of changes in Gamma pass rate, Average signal, Standard deviation for each case. Results: The average signal for each grid size showed difference levels of 0%, -0.19%, -0.04%, -0.46%, -8.32% and the standard deviation for each grid size showed difference levels of 0%, -0.30%, 1.24%, -0.70%, -7.99%. The gamma pass rate for each grid size showed difference levels of 0%, 0.27%, -1.43%, 5.32%, 5.60%. The gamma evaluation results according to distance in grid size range of 0.1 cm to 1.0 cm showed good agreement with reference condition (grid size 0.1 cm) within 1.5% and over 5% in case of the grid size was greater than 2.0 cm. Conclusion: We recognize that the grid size of gamma evaluation can make errors of IMRT QA. So we have to consider uncertainty of gamma evaluation according to the grid size and apply smaller than 2 cm grid size to reduce error and increase accuracy clinically.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.155-165
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• 1995

초모집단(superpopulation)으로 부터 반복적으로 유한모집단을 추출할 때, 이미 조사된 자료들을 이용하면 현재의 유한모집단 모수들을 ㄷ더 효율적으로 추정할 수 있다. 이러한 문제에 대하여 Ericson(1969)이 유한모집단 표본추출에서 베이지안 분석을 하였고, Ghosh와 Meeden(1986)은 정규 초모집단을 가정하여 유한모집단 평균의 경험적 베이즈 추정을 하였다. Nandram과 Sedransk (1993)는 Ghosh와 Meeden(1986)의 유한모집단들의 분산이 모두 같다는 가정들을 완화하여 유한집단 평균의 경험적 베이즈 추정을 하였다. 본 연구는 Nandram과 Sedransk의 결과를 층과표본추출의 경우로 일반화 하였다.

• Korean journal of applied entomology
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• v.54 no.3
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• pp.159-167
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• 2015

In order to establish B. tabaci control in paprika greenhouses a fixed-precision-level sampling plan was developed. The sampling plan consisted of spatial distribution analysis, a sampling stop line, and decision making. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 consecutive weeks, using 19 sampling locations in GH 1 and 9 sampling locations in GH 2. The plant in both greenhouses were divided into top (180-220 cm from the ground), middle (80-120 cm from the ground) and bottom (30-70 cm from the ground) sections and B. tabaci adults and pupae were observed on three paprika leaves at each position and recorded separately. GH 2 data were used to validate the fixed-precision sampling plan, which was developed using GH 1 data. In this study, spatial distribution analysis was performed using Taylor's power law with the pooled data of the top and bottom position (B. tabaci adults), and the middle and bottom positions (B. tabaci pupae), based on a 1-leaf sampling unit. Decision making was undertaken using the maximum of action threshold in accordance with previously published method, and the value was decided by the price of the plants. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated a reasonable level of precision.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.659-673
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• 1998

표본조사 교육의 효과적인 학습을 위하여 최근 많은 연구가 진행되고 있는 하이퍼미디어 시스템과 전문가 시스템의 특성을 적절히 결합하여 표본조사에 대한 교육과 응용분야에서 활용할 수 있는 표본조사론의 학습 및 실습을 위한 하이퍼미디어 전문가시스템의 개발을 시도해 보았다. 본 논문에서 구현한 하이퍼미디어 시스템은 멀티미디어 툴과 통계패키지를 결합한 시스템으로써 표본조사에 관한 전문적인 지식이 없고 통계 패키지의 사용에 익숙하지 않는 비전문가들에게 표본조사방법론에 대한 이론 학습 및 실습을 통하여 표본추출과정, 모수 추정, 표본크기의 결정 등 표본조사론 교육을 체계적이고 효과적으로 습득하게 해줄 뿐 아니라 실제 표본 조사된 자료로부터 실시간으로 모수를 추정할 수 있도록 해 주기 때문에 각종 표본조사에 보다 쉽게 활용할 수 있을 것으로 기대된다.

• Journal of Korean Society of Forest Science
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• v.46 no.1
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• pp.29-43
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• 1980

The sampling methods selected for this area was (1) Simple random sampling (2) Systematic sampling and (3) Sub-sampling. For the calculation of the number of sampling plot, 10 % coefficient of variation was adapted. As a result, 57 plots each for simple random sampling and systematic sampling was calculated. In the sub-sampling method, however, total of 40 plots, which were consisted of 5 Blocks, secondary 4 major units and tertiary 2 minor units, were examined. The reuslts obtained are summarized as follows : 1. The rate of expected error was 9.24% for simple random sampling, 8.36% for systematic sampling and 7.54% for sub-sampling, respectively. Therefore, the sub-sampling was proved to be the most accurate method among the test. 2. The volume calculated by each sampling method was compared to the volume of all stand. The rate of expected error was also lowest in the sub-sampling (0.39%), followed by systematic sampling (4.18%) and simple random sampling (7.92%). 3. Comparing the various reuslts and analysis of these results, the sub-sampling was regarded as the most rapid and economical method because this method had not only the least number of plots but also the least expected error among the tested sampling methods Therefore the sub-sampling is proved to be an ideal sampling method for forest survey.