• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.515-525
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• 2010

We investigated design-based properties of the ordinary least square estimator(OLSE) and the weighted least square estimator(WLSE) in a panel regression model. Given a complex data we derive the magnitude of the design-based bias of two estimators and show that the bias of WLSE is smaller than that of OLSE. We also conducted a simulation study using Korean welfare panel data in order to compare design-based properties of two estimators numerically. In the study we found the followings. First, the relative bias of OLSE is nearly two times larger than that of WLSE and the bias ratio of OLSE is greater than that of WLSE. Also the relative bias of OLSE remains steady but that of WLSE becomes smaller as the sample size increases. Next, both the variance and mean square error(MSE) of two estimators decrease when the sample size increases. Also there is a tendency that the proportion of squared bias in MSE of OLSE increases as the sample size increase, but that of WLSE decreases. Finally, the variance of OLSE is smaller than that of WLSE in almost all cases and the MSE of OLSE is smaller in many cases. However, the number of cases of larger MSE of OLSE increases when the sample size increases.

• Korean Journal of Environmental Biology
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• v.32 no.3
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• pp.211-215
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• 2014

In order to accurately estimate the litter mass, we evaluated the required sample sizes across 13 chronosequence stands for five years (1994~1996, 2003~2004) in northern hardwood forests in New Hampshire, USA. It was found that the number of required litter traps in our stands (0.25~0.5 ha) within ${\pm}10%$ of the sample mean was appeared to be similar or higher than the 15 litter traps installed in this study. Notably, in 1994 and 1995, the number of required litter trap was twice higher than the 15 litter traps. Further, within ${\pm}20%$ of the sample mean, the number of required litter traps was less than 10 across all 13 stands for five years, which indicates that we can reduce the sample size. Precisely, the number of sample size had increased in stands with steep and high elevation, but no relations with stand age across 13 stands were observed. Based on these results, we suggest that it is important to sample litter mass for several years, in order to determine the number of appropriate sample size, and stands with steep and high elevation may need more litter traps.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.28 no.3
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• pp.319-322
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• 1983

Species-area and species-quadrat number curves were used to determine the minimum sampling size and the minimum quadrat number for weed data collection in transplanted rice. In both cases, characteristic curves that first increased abruptly and then leveled off as fewer species were added with increased sampling size or quadrat number were obtained. Using these techniques, it was determined that three quadrats each 0.3㎡ (0.5m ${\times}$0.6m) in area were needed to adequately represent the weed community when it was sampled at rice heading.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.669-679
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• 2010

A sample survey design is suggested for the service satisfaction evaluation of regional education offices based on the sample size of 2009 Gyeongnam regional education offices's customer satisfaction survey. The sample design is developed to fit the goal of evaluation of individual regional offices and allocate at least the minimum sample size to each city or county in Gyeongnam to achieve the goal of the survey. The population is stratified according to the regions and the types of schools, and the sample of schools is selected with proportional to the size of classes within each stratum. Finally, each sample student is selected according to two-stage cluster sampling within each sample school. Weighting averages, weighting totals and so on can be evaluated for analysis purposes. Their variance estimates can be evaluated using re-sampling methods like BBR, Jackknife, linearization-substitution methods, which are generally used for the data from a complex sample.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.7-15
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• 2006

A large sample can Provide more information about the Population. As the sample size Increases, analysts will be more confident about the survey results. On the other hand, the costs for survey will increase in time and manpower. Therefore, determination of the sample size is a trade-off between the required accuracy and the cost. In addition, permitted error and significance level should be considered. Sample size determination in surveys for O/D estimation is also connected with confidence of survey result. However, the past methods were usually too simple to consider confidence. Therefore, a new method for O/D surveys was Proposed and it was accurate enough, but it has too large sample size when we have current budget constraint. In this research, several minimum sample size determination methods for origin-destination survey under budget constraint were proposed. Each method decreased sample size, but has its own advantages. Selection of the sample size will depend on the study Purpose and budget constraint.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.28-32
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• 2014

For a signal such as speech showing piece-wise linear shape in a very short time period, a nonuniform sampling method based on the inflection point detection (IPD) is proposed to reduce data rate. The method exploits the geometrical characteristics of signal further than the existing local maxima/minima detection (MMD) based sampling method. As results, the reconstructed signal by the interpolation of the IPD based sampled data resembles the original speech more. Computer simulation shows that the proposed IPD based method produces about 9~23 dB improvement over the existing MMD method. To show the usefulness of the IPD technique, it is applied to speech coding, and compared to the continuously variable slope delta modulation (CVSD). The nonuniformly sampled data is binary coded with one bit flag set "1". Noninflection samples are not sent, but only flag bits set 0 are sent. The method shows 0.3 ~ 9 dB SNR and 0.5 ~ 1.3 mean opinion score (MOS) improvements over the CVSD.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.94-100
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• 2001

When using a sample covariance matrix data in paucity of snapshots, adaptive matched field processing will have problem in inverting covariance matrix due to the rank deficiency. The general solutions are diagonal loading and eigenanalysis methods, but there is a significant bias in the power output. This paper presents a quantitative study of bias of power output and the performance of source localization through the simulation and the measured data analysis in fixed source case using the diagonal loading method for the minimum variance processor. Results show that the bias in power output is reduced and the performance of source localization is improved when the number of snapshots is greater than the number of array sensors.

• Journal of Food Hygiene and Safety
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• v.30 no.2
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• pp.127-131
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• 2015

This study aimed to calculate the required sample size to monitor food items during risk assessment studies. Based on a data set from a previous study (2,400 data points for heavy metal assessment from 17 food items), the required sample size was estimated by using a single equation with the standard deviation value, error range, and 95%-99% confidence intervals. The required sample size was calculated with each of the heavy metals for the assessment. The results showed that cadmium, lead, and mercury of required sample sizes for further monitoring were range of 7-90, 7-1, 062, and 11-238, respectively. We found that the required sample size varied depending on the standard deviation of the previous monitoring data. This study provides a basic method to determine the minimum sample size required in food monitoring to devise practical sampling strategies.

• 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.