• The Journal of Korean Obstetrics and Gynecology
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• v.25 no.1
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• pp.70-78
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• 2012

Objectives: The purpose of this article is not until to investigate the changes and types of statistical methods and to point out the statistical errors after analyzing the method of articles that improve the quality of the statistical analysis of papers published in the Journal of Oriental Obstetrics and Gynecology. Methods: Papers published in the Journal of Oriental Obstetrics and Gynecology from 2009 to 2011 were reviewed for methodological and statistical validity using a modified version of Ahn's checklist. A statistician reviewed individual papers and evaluated the list items in the checklist for each paper. To avoid the potential assessment error by the statistician who lacks expertise in the field of Oriental Obstetrics and Gynecology. Results: A total of 190 papers including 64 original articles, 40 reviews article, 58 case report and 28 brief communication were reviewed. Statistics methods used in 121 papers were composed of t-test(58.7%), ANOVA test(19.8%) and ${\chi}^2$- test (14.0%) et al. Whereas only 14.9% of papers were free of statistical errors, the number of omission errors was 58 and the number of commission errors was 149 each. Conclusions: A variety of statistical errors were encountered in papers published in the Journal of Oriental Obstetrics and Gynecology. Accordingly, researchers should be more careful when it comes to describing and applying statistical methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.284-294
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• 2018

Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.533-542
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• 1999

Widespread of internet causes rapid changes in many areas of statistics such as statistical computation and education. In this paper the efficient methods for statistical software development on the internet environment are introduced. Also the developed examples about monte-carlo permutation tests for two-way contingency tables using Microsoft COM (Component Obejct Model) technology are presented.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.355-366
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• 2002

The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.437-447
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• 2009

Recently, in addition to analyzing data with appropriate statistical methods, statistical analysts in the industrial fields face difficulties that they have to compose proper datasets for analysis objectives via extracting or generating processes from diverse data storage devices. In this paper we survey and compare many state-of-the-art data access technologies adopted by several commonly used statistical packages. More understanding of these technologies will help to reduce the costs occurring when analyzing large size of datasets in especially data mining works, and so to allow more time in applying statistical analysis methods.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.23-35
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• 2003

This paper provides the checklist of statistical methods in the water environmental research of Han and Nakdong river basins in South Korea. There are many errors pointed out in adopting statistical methods for the researches, as an example, basic statistical assumptions are missed for t-tests or regression analyses. Some new ideas are proposed for better researches of the river basins in Korea.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.17-33
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• 2001

The characteristics of Weibull distribution are investigated as a function of shape parameter. The statistical estimation methods of the shape parameter and statistical comparison methods of two or more shape parameters are studied. Assuming Weibull distribution, statistical analysis of bending-strength data of alumina titanium carbide ceramic matrix composites machined two different methods are performed.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.859-869
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• 2000

In this paper, various methods for finding confidence intervals for p of binomial parameter are reviewed. Also we introduce tow bootstrap confidence intervals for p. We compare the performance of bootstrap methods with other methods in terms of average coverage probability by Monte Carlo simulation. Advantages of these bootstrap methods are discussed.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.221-244
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• 2016

Purpose: This research reviews the papers, published in the Journal of the Korean Society for Quality Control (KSQC) and the Journal of the Korean Society for Quality Management (KSQM) since 1965, in the area of statistical methods. The literature review is performed in the four fields of the statistical methods and we categorize the published articles into the several sub-areas in each field. Methods: The reviewed articles are classified into the four main categories: probability model and estimation, Bayesian analysis and non-parametric analysis, regression and time series analysis, and application of data analysis. We examine the contents and relationships of the published articles of the several sub-areas in each category. Results: We summarize the reviewed papers in the chronological road-maps for each sub-area, and outline the relations of the connected papers. Some comments on the contents and the contributions of the reviewed papers are also provided in this paper. Conclusion: Various issues are employed and published on the research of the application statistical methods for past 50 years, and many worthy works are achieved in the theory and application areas of statistical methods for improving quality in the manufacturing and service industries. The future direction of the research in the statistical quality management methods also can be explored by the contents of this research.