• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.2
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• pp.140-146
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• 2005

The aim of our study understands the influence of meteorological factors relating to the formation of the red tide, and monitors the red tide by satellite remote sensing. The meteorological factors have directly influenced on red tide formation. Thus, it was possible to predict and apply to red tide formation from statistical analyses on the realtionships between red tide formation and meteorological factors, and also to realize the near real time monitoring for red tide by satellite remote sensing.

• Journal of the Korean Statistical Society
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• v.4 no.2
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• pp.127-138
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• 1975

There have been a number of studies and analysis designed to explain imports and exports disaggregated by commodities in many countries. These analyses, however, all concentrate on the trading patterns of industrial countries, and there has been very little of systematic analyses of the imports and exports by types of commodities for developing countries. There is, of course, an obvious reason for ignoring these countries, and that has to do with the availability, or rather paucity, of adequate data; it is widely known that the data on prices of disaggregated imports and exports are most difficult to obtain. The purpose of this paper is to study and analyze the behavior of the imports of Korea at disaggregated levels during the period 1965-1974. Data on imports at a disaggregated level have recently been made available in Korea for a seven-commodity breakdown. These seven categories cover some 90% of the total Korean imports.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.40-47
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• 2006

Claim history data of rather long period were collected to assess reliability and warranty cost analyses. The data were appropriately organized to be used for further statistical analyses. For each critical component, nonparametric statistical method was applied to obtain reliability plot. Hazard plots of the components in a subsystem or system level were also obtained. Competing risk model was assumed to obtain the performance of the subsystem or system level.

• Journal of Korean Society for Atmospheric Environment
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• v.7 no.1
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• pp.23-30
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• 1991

The major purpose of this study is to delineate and assess the regional $SO_2$ levels in Seoul. This study is based on 1988 year-round data from 20 air quality continuous monitoring stations in Seoul. Statistical analyses were attempted, statistical parameters such as average concentration, standard deviation, maximum concentration, minimum concentration and monthly highest concentration were included in the analyses. In addition, Larsen's averaging time analysis was evaluated in terms of 24-hr concentration. The $SO_2$ levels in 1988 were that most stations except Daechidong, Sinlimdong, Jamsil 2, Bangidong violate the long-term standard (annual average 0.05 ppm) and the percentage of number of days within a year in which the 24-hr average concentration observed exceeds short-term standard (0.15 ppm) are; 37% at Deungchondong, 30% at Sinseoldong, mor than 20% at Ssangmundong, Myunmogdong and Oryudong.

• KIEAE Journal
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• v.7 no.3
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• pp.31-37
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• 2007

Statistical analyses with actual data are used in estimating construction cost for many years, but collected data could include factors that distort analytical results, namely outliers. To enhance reliability in predicting construction cost, the methodology, which is able to identify outliers and determine how to manage them, is needed. Actual costs obtained from 22 construction projects were studied. It is found that there is substantial disparity between results considering outliers and results not considering ones. Therefore, it is to identify outliers and apply an optimum process in estimating construction cost when actual data is used in statistical analysis.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.195-210
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• 1999

The multiplicity of software packages brings about a choice problem to the end-user and a multi-fold intensity to the competing developer. This study intends to provide guidelines solving the problems for both the end-user and the developer of packages for automatic statistical analyses. For the purpose, we adopt an appropriate evaluation model in terms of user-perceived quality through the applicable criteria and an evaluation method. The result of empirical study is described, which shows that the weight of each criterion is dynamic along usage levels. Briefly, functionality, usability, and reliability are key factors to contribute to the perceived quality. The empirical study also illustrates a comparative analysis on the dominant products, SAS and SPSS, in Korea.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.103-129
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• 2019

The main goal of a case-control study is to learn the association between various risk factors and a primary outcome (e.g., disease status). Particularly recently, it is also quite common to perform secondary analyses of the case-control data in order to understand certain associations between the risk factors of the primary outcome. It has been repeatedly documented with case-control data, association studies of the risk factors that ignore the case-control sampling scheme can produce highly biased estimates of the population effects. In this article, we review the issues of the naive secondary analyses that do not account for the biased sampling scheme, and also the various methods that have been proposed to account for the case-control ascertainment. We additionally compare the results of many of the discussed methods in an example examining the association of a particular genetic variant with smoking behavior, where the data were obtained from a lung cancer case-control study.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.156-168
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• 2004

This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.3
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• pp.207-215
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• 1993

In order to statistically predict $O_3$ levels in Seoul, the study used the TMS (telemeted air monitoring system) data from the Department of Environment, which have monitored at 20 sites in 1989 and 1990. Each data in each site was characterized by 6 major criteria pollutants ($SO_2, TSP, CO, NO_2, THC, and O_3$) and 2 meteorological parameters, such as wind speed and wind direction. To select proper variables and to determine each pollutant's behavior, univariate statistical analyses were extensively studied in the beginning, and then various applied statistical techniques like cluster analysis, regression analysis, and expert system have been intensively examined. For the initial study of high level $O_3$ prediction, the raw data set in each site was separated into 2 group based on 60 ppb $O_3$ level. A hierarchical cluster analysis was applied to classify the group based on 60 ppb $O_3$ into small calsses. Each class in each site has its own pattern. Next, multiple regression for each class was repeatedly applied to determine an $O_3$ prediction submodel and to determine outliers in each class based on a certain level of standardized redisual. Thus, a prediction submodel for each homogeneous class could be obtained. The study was extended to model $O_3$ prediction for both on-time basis and 1-hr after basis. Finally, an expect system was used to build a unified classification rule based on examples of the homogenous classes for all of sites. Thus, a concept of high level $O_3$ prediction model was developed for one of $O_3$ alert systems.