• Korea journal of population studies
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• v.28 no.1
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• pp.203-233
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• 2005

기존 연구에 의하면 중국 여성의 사회적 지위는 높게 평가된다. 그러나 실증적인 자료에 근거하여 이루어진 중국 여성의 가족 내 지위에 대한 연구는 매우 부족하다. 이 연구는 중국 여성의 지위에 대한 균형적인 시각을 얻기 위하여 가족 내 여성의 지위를 알아보고자 한다. 가족 내 여성의 지위를 파악하기 위하여 아버지의 자녀 양육과 자녀교육 관련 의사결정 과정에의 참여를 중심으로 성역할 분담을 살펴보았다. 이를 위하여 6개 도시 지역과 농촌 지역에서 수집된 자료의 통계 분석와 상해 산동 지역에서의 포커스 그룹 인터뷰가 통합적으로 이용되었다. 연구의 결과는 다음과 같다. 첫째, 지역에 관계없이 중국 사회에서 자녀 양육의 주책임은 어머니에게 있다. 둘째, 아버지들은 자녀 양육 활동보다 의사결정 과정에 더 높은 참여율을 보인다. 셋째, 아버지의 자녀 양육 참여율은 농촌에 비해 도시 지역에서 높게 나타난다. 반면, 의사결정의 경우는 도시에 비해 농촌 지역 아버지들의 참여율이 더 높다. 넷째, 전통적인 성역할 구분에 대한 가치관도 도시와 농촌 지역간에 차이가 있다. 결과적으로 중국 가족 내 여성의 지위는 지역별로 차이가 있는 것으로 보이며, 중국 가족에서 자녀 양육 책임이 동등하게 분담되지 않아서 여성의 이중부담이 큰 것으로 생각된다.

• Journal of the Korean Society of Radiology
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• v.84 no.4
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• pp.784-791
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• 2023

Based on statistics available in Korea, trauma centers play a critical role in treatment of patients with trauma. Interventional radiologists in trauma centers perform various procedures, including embolization, which constitutes the basic treatment for control of hemorrhage, although interventions such as stent graft insertion may also be used. Although emergency interventional procedures have been used conventionally, rapid and effective hemorrhage control is important in patients with trauma. Therefore, it is important to accurately understand and implement the concept of damage control interventional radiology, which has gained attention in recent times, to reduce preventable trauma-induced mortality rates.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1147-1161
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• 2015

Nowadays we are considering and analyzing not only classical data expressed by points in the p-dimensional Euclidean space but also new types of data such as signals, functions, images, and shapes, etc. Symbolic data also can be considered as one of those new types of data. Symbolic data can have various formats such as intervals, histograms, lists, tables, distributions, models, and the like. Up to date, symbolic data studies have mainly focused on individual formats of symbolic data. In this study, it is extended into datasets with both histogram and multimodal-valued data and a divisive clustering method for the mixed feature-type symbolic data is introduced and it is applied to the analysis of industrial accident data.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.353-369
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• 2000

We systematized an stratified spatial sample design(SSSD) that uses the adequate stratification criteria such as the shapeness or the dispersion of an interesting region in a spatial population. And we proposed an adaptive searching estimation method in the SSSD to estimate the area of region of interest in two-dimensional surfaces. When wc adopt the proposed adaptive searching estimation method in SSSD, the observing sample size is more decreased than a classical sample design that all the designed sample size is observed. Nevertheless it has been shown that we can produce the moderate result but the efficiency is a slight reduced.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.607-615
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• 2005

Recently the interval estimation of a binomial proportion is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the will-known Wald confidence interval. Various alternatives have been proposed. Among them, Agresti-Coull confidence interval has been recommended by Brown et al. (2001) with other confidence intervals for large sample, say n $\ge$ 40. On the other hand, a noninformative Bayesian approach called Polya posterior often produces statistics with good frequentist's properties. In this note, an interval estimator is developed using weighted Polya posterior. The resulting interval estimator is essentially the Agresti-Coull confidence interval with some improved features. It is shown that the weighted Polys posterior produce an effective interval estimator for small sample size and a severely skewed binomial distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1972-1976
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• 2007

정확한 수문자료를 예측하기 위한 많은 연구들이 현재까지 진행되어 왔다. SVM(Support Vector Machine)은 그 구조가 신경망과 유사하나 신경망과는 다르게 철저히 통계적, 수학적 이론에 기반을 두고 있고 비선형예측 모형이며 지역해 문제가 발생하지 않는 다는 점 등으로 인해 상당히 견고한 모형으로 평가받고 있다. 본 연구에서는 두 경우의 수문시계열 자료를 이용하여 전통적인 통계학적 모형과 신경망 모형 그리고 수문학 분야에서는 아직까지 적용된 사례가 매우적은 SVM 모형의 예측 결과 비교를 통해 모형의 장단점을 평가하였다. 비교 결과 SVM 모형은 수문시계열 자료 예측에 있어서 기존의 방법들에 비해 안정적이고 정확한 예측 결과를 보여 주었다.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.67-81
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• 2006

The present study suggests an analytical method to overcome the spatial problems that traditional hedonic methods have. The concept of overlapping neighborhoods is introduced in order to solve the problems of global parameter estimate methods that treat the whole city by the gross. Moreover, a 3rd party program for the tight coupling of GIS and statistics is developed in order to explore hedonic methods efficiently. By using these, this study analyses the spatial variation of location variables that affect the real estate price. The results show that the influences of urban centers do not reach to the whole city, but only to the catchment areas of them. And the coefficients of location variables are different depending on the space. The tight coupling of GIS and statistics offers a powerful tool in analysing the real estate price efficiently.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.835-844
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• 2010

Tools for statistical analysis of extreme values include the classical annual maximum method, the modern threshold method and variants improving the second one. While the annual maximum method is to t th generalized extreme value distribution to the annual maxima of a time series, the threshold method is to the generalized Pareto distribution to the excesses over a high threshold from the series. In this paper we deal with the Poisson-GPD method, a variant of the threshold method with a further assumption that the total number of exceedances follows the Poisson distribution, and apply it to the daily percentage increases and decreases computed from the spot prices of West Texas Intermediate, which were collected from January 4th, 1988 until December 31st, 2009. According to this analysis, the distribution of daily percentage increases as well as decreases turns out to have a heavy tail, unlike the normal distribution, which coincides well with the general phenomenon appearing in the analysis of lots of nowaday nancial data.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.53-60
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• 2018

In order to manage energy efficiency by analyzing the amount of energy, it would determine the nature of the factors involved in the energy utilization. Therefore, accurate measurement of the energy consumption data is an important factor in the energy management. In this study, we are aware of the importance of the data measurement, and proposes the accuracy assessment of electric energy monitoring system. According to conventional statistical methods it is proceeded as follows; i)the measurement error value would be determined by a random variable, ii) setting the confidence interval to consider the distribution of the statistic and determines the confidence level of the measurement accuracy. And using the t-distribution CDF is used to facilitate even small sample data.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1115-1129
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• 2009

Previous research has recently shown that non-cognitive factors such as attitudes toward statistics contribute positively to statistics learning, Hence, helping students develop positive attitudes toward statistics has become one of the essential goals of statistics teaching. A wide variety of instruments assessing attitudes toward statistics were developed and validated in foreign countries, but not many in Korea. The SATS-36(Survey of Attitudes Toward Statistics-36; Schau et al., 1995) has been regarded as one of the most valid measures of attitudes toward statistics. Therefore, this study was designed to validate a Korean version of Survey of Attitudes Toward Statistics(K-SATS). Instead of six factors of the original scale, a five-factor structure including interests, value, cognitive competence, difficulty, and effort was empirically supported by the Korean student sample. The results evidenced high reliability and construct validity of K-SATS. In addition, students' attitudes towards statistics differed across gender, level of statistics courses, degree programs, and major. These findings were discussed in terms of their implications for future research and statistics teaching.