• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.225-234
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• 2014

We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of large and complex data has attracted significant interest. Symbolic Data Analysis (SDA) was proposed by Diday in 1980's, which provides a new framework for statistical analysis. In SDA, we analyze an object with internal variation, including an interval, a histogram and a distribution, called a symbolic object. In the study, we focus on a cluster analysis for distribution valued dissimilarities, one of the symbolic objects. A hierarchical clustering has two steps in general: find out step and update step. In the find out step, we find the nearest pair of clusters. We extend it for distribution valued dissimilarities, introducing a measure on their order relations. In the update step, dissimilarities between clusters are redefined by mixture of distributions with a mixing ratio. We show an actual example of the proposed method and a simulation study.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1191-1199
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• 2010

Knowing what factors into a player's ability to affect the outcome of a sports game is crucial. This knowledge helps determine the relative degree of contribution by each team member as well as sets appropriate annual salaries. This study uses statistical analysis to investigate how much the outcome of a professional baseball game is influenced by the records of individual players. We used the Lotte Giants' data on 252 games played between 2007 and 2008 that included environmental data(home or away games and opponents) as well as pitchers' and batters' data. Using a SAS Enterprise Miner, we performed a logistic regression analysis and decision tree analysis on the data. The results obtained through the two analytic methods are compared and discussed.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.549-557
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• 2011

In this paper, we apply cluster analysis to "Okayama parking data" that is one of the spatial point patterns data that includes locations and the fare structure of car parking space in Okayama central area. This study classifies the characteristics of small areas through Okayama parking data as well as visualizes the results of the cluster analysis. We develop web applications that connect the results of a cluster analysis and overlay objects including points of balloons and rectangles of small areas over a map of Okayama central area.

• Transactions of Materials Processing
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• v.19 no.8
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• pp.523-528
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• 2010

The forging industry is composed of those plants that make parts to order for customers; or make parts for their own company's internal use; or make standard parts for resale. Also, the forging industry is closely related with automobile industry and ship building industry - Korea's major export industry. But, it is hard to find the Korea's forging industry's statistical analysis because it is not revealed with final product. In this paper, we perform statistical analysis using the micro data service provided by the Statistics Korea. We focus on the analysis of production costs as well as the status of forging company and their employee.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.117-129
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• 1996

This Study intends to analysis what 3 factors, which are indices of Capital, Labor and Distribution, really affect to Value-Added Productivity through Statistical Analysis. For this, We selected 12 indices of Value-Added from the edition of 'Annual report of Korean companies' published in 'Korea Investors Service., Inc', especially in parts of Chemicals and Chemical products of total 85 companies. Using this data, Multivariate Statistical Analysis such as Principal Component Analysis, Factor Analysis, Covariance Structure Analysis is taken for modeling the effect of 3 factor(Labor Productivity, Capital Productivity and the Index of Distribution) on Value-Added Productivity.

• Journal of KSNVE
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• v.8 no.4
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• pp.609-615
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• 1998

In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis(DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.1
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• pp.33-39
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• 2003

Interior parts of a vehicle are getting important to reduce interior noise. Therefore, prior analysis of cabin noise related with interior parts are necessary at first design stage. Recently, Statistical Energy Analysis(SEA) has been suggested as a possible way for high frequency range noise analysis of interior parts. The validity of noise analysis with SEA to interior parts has been preyed by comparing with experimental result, and the developed method with SEA has been applied in finding optimized interior parts package.

• Journal of Preventive Medicine and Public Health
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• v.54 no.3
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• pp.166-172
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• 2021

Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major components-the exposure and outcome-have recently evolved to ascertain the in-between process, which can explain the underlying causal pathway. Mediation analysis has emerged as a compelling method to disentangle the complex nature of these pathways. The statistical method of mediation analysis has evolved from simple regression analysis to causal mediation analysis, and each amendment refined the underlying mathematical theory and required assumptions. This short guide will introduce the basic statistical framework and assumptions of both traditional and modern mediation analyses, providing examples conducted with real-world data.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.153-159
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• 2009

The purpose of this paper is to suggest the problems of basic population data(1960-2005) and the data(2006-2050) of population projections reported by Korean National Statistical Office in November 2006. The errors on the basic population data can be easily checked by using the graphical analysis and the method of linear regression analysis. It is necessary to revise the population projections reported by Korean National Statistical Office.

• International Journal of Safety
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• v.6 no.2
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• pp.13-16
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• 2007

This study focuses on the trends and issues of improving safety management of elevators in Korea. Frequency and severity of accidents in relation to conditional pass in periodic inspection, maintenance, market surveillance are analyzed based on the statistical data and social cost due to a variety of related fields in managing elevator safety was estimated first. The results of statistical analysis performed in this study will provide logical basis and future direction for improving the safety management system. The role of certification and supervision is particularly addressed to reduce the related accidents and the social cost. The effectiveness of such procedures can be found from the results of simple statistical analysis.