• 한국연초학회지
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• 제23권1호
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• pp.53-59
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• 2001

To decrease of deviations from target specifications and excessive variability around targe, we exclusively designed statistical process control system involving general manager and expert tool for cigarette manufacturing process. This system is a unique programming environment for the development of total process control software including various control charts according to data type and process capability analysis. Also this system includes the statistical analysis module to analyze defective causes immediately when inferior products are made and the module to offer regular reports. This system is customized considering the manufacture environment based on the opinions of workers.

• 응용통계연구
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• 제11권2호
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• pp.389-401
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• 1998

본 논문에서는 멀티미디어를 활용한 회귀분석 학습시스템 CybeRClass(Cyber Regression Class)를 소개하고자 한다. CybeRClass는 음성정보와 애니메이션 등을 활용하여 회귀분석에 대한 학습을 시켜주는 시스템이다. 이 시스템은 군집분석이나 판별분석 등의 다변량분석 학습이 가능하도록 설계되었다. 멀티미디어 기술을 위한 도구로는 Multimedia ToolBook을 사용하였으며, 통계계산과 통계그라픽을 위해서는 객체지향 통계 언어인 Xlisp-Stat을 사용하였다.

• Journal of Preventive Medicine and Public Health
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• 제46권2호
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• pp.96-104
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• 2013

Objectives: The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures. Methods: This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010. Results: Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses. Conclusions: Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.

• 한국한의학연구원논문집
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• 제18권3호
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• pp.127-132
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• 2012

Background and Purpose : This study was to investigate statistical validities and trends of previously reported papers that used various statistical techniques such as t-test and analysis of variance. Methods : To analyze the statistical procedures, 38 original articles using those statistical methods were selected from Journal of Korea Institute of Oriental Medicine(JKIOM) published from 2010 to 2012. Results : Analysis of variance and t-test were used in 20 papers (38.5%), 16 papers (30.8%) of 52 papers. Four articles(10.5%) did not report ${\alpha}$ values and nineteen papers(50.0%) of 38 ones were not tested for normal distribution. Five papers (13.2%) misused t-test and 3 papers (7.9%) did not carry out the multiple comparison. Conclusions : To improve the quality of JKIOM, The participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.

• 대한안전경영과학회지
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• 제15권1호
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• pp.283-292
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• 2013

This paper aims to propose a new steps of hypothesis testing using analysis process and improvement process in the six sigma DMAIC. The six sigma implementation models proposed in this paper consist of six steps. The first step is to establish a research hypothesis by specification directionality and FBP(Falsibility By Popper). The second step is to translate the research hypothesis such as RHAT(Research Hypothesis Absent Type) and RHPT(Research Hypothesis Present Type) into statistical hypothesis such as $H_0$(Null Hypothesis) and $H_1$(Alternative Hypothesis). The third step is to implement statistical hypothesis testing by PBC(Proof By Contradiction) and proper sample size. The fourth step is to interpret the result of statistical hypothesis test. The fifth step is to establish the best conditions of product and process conditions by experimental optimization and interval estimation. The sixth step is to draw a conclusion by considering practical significance and statistical significance. Important for both quality practitioners and academicians, case analysis on six sigma projects with implementation guidelines are provided.

• 응용통계연구
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• 제20권3호
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• pp.619-634
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• 2007

자료분석과정에서 그래프의 이용은 필수적이라고 하겠다. 다양하게 개발된 수많은 그래픽 기법들을 적절하게 사용할 수 있다면 한 단계 업그레이드된 통계분석이 가능할 것이며, 이런 면에서 볼 때 통계그래픽스는 통계학을 전공하는 학생들에게 꼭 필요한 강좌라고 할 수 있다. 다양하게 개발된 그래픽 기법의 막강한 파워를 제대로 느끼기 위해서는 적절한 통계 소프트웨어의 선택이 매우 중요한 문제라고 할 수 있는데, 뛰어난 그래픽 기능이 있는 R을 사용하는 것이 효율적으로 다양한 그래픽 기법을 구현할 수 있는 가장 바람직한 선택이라고 하겠다. 이 논문에서는 통계 그래픽스를 R을 이용하여 구현하는 강좌를 개설하고자 하는 경우에 사용할 수 있는 적절한 교과내용을 제안하고, 어떤 방식으로 강의하는 것이 가장 효과적인지에 대한 고민을 함께 해 볼 수 있는 기회를 제공하고자 한다.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• 한국임상수의학회지
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• 제26권3호
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• pp.189-199
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• 2009

With the growing importance of evidence-based medicine, clinical or biomedical research relies critically on the validity and reliability of data, and the subsequent statistical inferences for medical decision-making may lead to valid conclusion. Despite widespread use of analytical techniques in papers published in the Journal of Veterinary Clinics statistical errors particularly in design of experiments, research methodology or data analysis methods are commonly encountered. These flaws often leading to misinterpretation of the data, thereby, subjected to inappropriate conclusions. This article is the first in a series of nontechnical introduction designed not to systemic review of medical statistics but intended to provide the journal readers with an understanding of common statistical concepts, including data scale, selection of appropriate statistical methods, descriptive statistics, data transformation, confidence interval, the principles of hypothesis testing, sampling distribution, and interpretation of results.

• 응용통계연구
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• 제6권2호
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• pp.443-452
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• 1993

비학술단체에서 통계자료의 수집과 분석시에 반드시 고려해햐할 항목을 나열한 점검표를 개발하였다. 개발된 점검표를 활용하여 광주, 전남지역의 단체, 언론, 금융기관, 산업체에서 일년간(1991년 4월 5일부터 1992년 4월 4일까지) 통계조사결과 발표된 결과물에 대하여 자료수집과 분석의 타당성을 검토하였다.

• Advances in nano research
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• 제14권3호
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.