본 연구는 축구화 브랜드의 3i 모델의 효과성을 검증하여 브랜드의 3i 모델 중요성과 시사점을 도출하여 축구화 브랜드 전략의 기본 자료를 제공하고자 했다. 따라서 지난 3년 동안 축구화를 구매한 경험이 있는 대상자를 표본으로 선정했으며, 421부의 자료를 최종분석에 적용했다. 자료처리는 빈도분석, 내적일관성, 확인적 요인분석, 상관분석, 구조방정식 모형 분석을 실시했으며, 모든 분석은 SPSS 및 AMOS(ver. 21.0) 프로그램을 활용했다. 연구결과 첫째, 축구화 브랜드의 3i 모델이 브랜드 신뢰에 유의한 영향을 미치는 것으로 나타났다. 둘째, 브랜드 신뢰는 소비자 구매행동에 유의한 영향을 미치는 것으로 나타났다. 셋째, 축구화 브랜드의 3i 모델은 소비자 구매행동에 유의한 영향을 미치는 것으로 나타났다. 마지막으로, 축구화 브랜드3i 모델과 소비자 구매행동 간의 브랜드 신뢰는 부분적인 매개효과가 있는 것으로 나타났다.

The purpose of this study is to understand the production efficiency of individual fishing communities and provide directions for improvement. The subject of the study is aquaculture type Ochon-Gye in Goheung-gun. The analysis method used bootstrap-DEA to overcome the statistical reliability problem of the traditional DEA analysis technique. In addition, data mining-GIS was applied to identify the spatial productivity of fishing communities. The values of technology efficiency, pure technology efficiency, and scale efficiency were estimated for 32 aquaculture-type fishing villages. Then, using the benchmarking reference set and weights, the projection was presented through adjustment of the input factor excess, and furthermore, the confidence interval of the efficiency values considering statistical significance was estimated using bootstrap.

The purpose of this study is to analyze the efficiencies of project management offices in large information system construction projects using the data envelopment analysis. In addition, we tried to estimate the confidence interval of those efficiencies using bootstrap DEA to give a statistical meaning. The efficiency by the CCR model is analyzed as eight project management offices are fully efficient and 22 project management offices are inefficient. On the other hand, there are 15 project management offices are fully efficient, but 15 project management offices are inefficient in the BCC model. As the result of the scale efficiencies, of the inefficient project management offices, 13 project management offices are inefficient in scale. It is possible to eliminate the inefficiency in the CCR model by improving their project performances. And, the nine project management offices showed that the inefficiency was due to pure technical efficiency, and these companies should look for various improvements such as improvement of project execution system and project management process. In order that the inefficient project management offices be efficient, it is analyzed that more efforts must be made for on-budget and on-time as a result of examining the potential improvement potentials of inefficient project management offices.

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

  ANOVA is widely used for measurement system analysis. It assumes that the measurement error is normally distributed, which may not be seen in certain industrial cases. In this study, the exact and bootstrap confidence intervals for precision-to-toleranc

Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and analysis. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this paper, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with ASP for user to handle easily in manufacturing system.

Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and education. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this study, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with java applet for user to handle easily.

Statistical process cintrol is intended to assist operators of a stable system in monitoring whether a change has occurred in the process, and it uses several control charts as main tools. In design and use of control chart, it is rational that probabilit

In this study, we establish bootstrap control limits for robust M-estimator chart by applying the bootstrap method, called resampling, which could not demand assumptions about pre-distribution when the process is skewed and/or the normality assumption is doubt. The results obtained in this study are summarized as follows : bootstrap M-estimator control chart is developed for applying bootstrap method to M-estimator chart, which is more robust to keep Type Ⅰ error when process contain contaminate quality characteristic.

하나의 콘텐츠를 여러 디바이스에서 동일하게 사용하고 싶은 편리함에 대한 요구는 디스플레이 종류에 따라 화면의 크기를 자동으로 최적화하는 웹페이지 기술인 반응형 웹을 탄생시켰다. 유행의 속도가 빠른 한국은 IT기술의 사용 속도 면에서도 세계 어느 나라보다도 빠른 변화를 경험하고 있으며, 2010년 에단 마코트(Ethan Marcotte)에 의해 소개된 반응형 웹의 기 술은 이미 한국에서 상용화 되고 있다. 하지만 반응형 웹의 제작에 대한 표준화된 가이드나 개발 모델은 아직 미비하며, 제작 면에서도 표준화된 프로세스 보다는 제작자 개개인의 역량에 의존한 개발의 성격이 강한 현실이다. 본 연구에서는 반 응형 웹의 대표적 오픈 플랫폼인 부트스트랩(Bootstrap)의 사례를 기반으로 하여 반응형 웹의 그리드 시스템을 분석하고, 황금비율과 유동형 레이아웃을 중심으로 반응형 웹의 그리드 시스템 모델을 제안하였다. 늘어나는 수요와 중요성에도 불구 하고 관련 연구와 프로세스 표준화 작업이 부족한 반응형 웹의 제작환경에서, 프레임워크인 부트스트랩의 그리드 시스템은 반응형 웹 제작의 프로세스 표준화 작업에 좋은 선행연구 자료가 될 수 있을 것으로 보인다. 또한, 현재 서비스 중인 사이 트인 ‘클라우드 제트(Cloud Z)’에 대한 사례분석은, 부트스트랩을 사용하여 제작되는 반응형 웹 사이트가 현장에서 고객의 요구사항과 어떻게 조율되는지 대한 실제적인 사례라는 점에서 의미 있는 자료로 보여 진다.

Bootstrap methods is the computer-based resampling method that estimates the standard errors and confidence intervals of summary statistics using the plug-in principle for assessing the accuracy or uncertainty of statistical estimates, and the BCa method among the Bootstrap methods is known much superior to other Bootstrap methods in respect of the standards of statistical validation. Therefore this study suggests the method of the representation and treatment of uncertainty in flood risk assessment and water resources planning from the construction and application of rainfall frequency analysis model considersing the uncertainty based on the nonparametric BCa method among the Bootstrap methods for the assessement of the estimation of probability rainfall and the effect of uncertainty considering the uncertainty of the parameter estimation of probability in the rainfall frequency analysis that is the most fundamental in flood risk assessement and water resources planning.

본 연구에서는 부트스트랩(Bootstrap) 기법을 이용하여 측우기 강우량 관측계열(CWK)과 근대우량계 강우량 관측 계열(MRG)에 대해 동질성 분석을 실시하였다. 서로 다른 두 자료계열에 대한 전통적인 통계적 동질성 검정 방법은 모집단의 분포형을 알고 있어야 검정결과가 유효하였기 때문에 모집단의 분포가 복잡한 기상자료들은 이러한 전통적 방법을 사용하여 동질성을 파악하는 것이 매우 어려웠고 결과로 제시된 통계적 유의성에 대해서도 의심의 여지가 있었다.

본 연구에서는 Monte-Carlo 모형, AR(1)모형, PAR(1) 모형과 같은 추계학적 모형의 잔차값을 무작위적 복원추출하여 연 및 월 하천 유출량자료를 모의발생하였다. Bootstrap이라고 불리우는 이 복원추출방법은 자료의 모집단의 가정이 필요없다는 장점이 있으며 자료로부터 직접 통계적 분포형을 추정하는 방법으로써 자료의 순위변동법을 이용한다. 본 연구에서는 이 방법을 용담지점에 적용하였으며 Bootstrap 방법으로 모의발생된 하천 유출량자료