• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.121-141
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• 1990

Computer intensive bootstrap methods are studied as a tool of statistics. Practical calculation and theoretical justification problem of the methods in estimating the sampling distribution and construction confidence region of parameters are discussed through several examples. Statistical meaning of the methods are also considered.

• Journal of Power System Engineering
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• v.13 no.5
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• pp.59-66
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• 2009

High temperature and pressure valves in power plant have been used for fluid flowing and leakage occurred owing to valve internal damage such as disc wear, crack and inserting of foreign objects etc. in these valves. Recently, multi-measuring technique applied both ultrasonic and acoustic method have been used for evaluation of valve internal leakage in order to raise measurement reliability. Therefore, we have performed various leakage tests using ultrasonic and acoustic measuring system and acquired leakage data for the various leakage conditions. In this study, we developed the estimation method of regression model through leakage data, and expectation method for valve opening ratio, which is directly proportion to leakage rate, using the established estimation model from the measured data, valve size and fluid pressure so as to enhance data reliability. As a result of this study, it was founded that expectation method of leakage rate by statistical analysis method is appropriate to valve leakage evaluation.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.389-402
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• 2023

Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.

• Journal of Veterinary Clinics
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• v.26 no.3
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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.

• 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 the Korea Society of Computer and Information
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• v.22 no.11
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• pp.125-133
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• 2017

Recently, as the programming education has become essential in school, discussion of how to teach programming has been important. This study performed a meta-analysis of the effect size depending on the teaching and learning method for the programming education. 78 research data selected from 45 papers were analyzed from cognitive and affective aspects according to dependent variables. The analysis from the cognitive aspect showed that there was no statistically significant difference in the effect size depending on whether or not the teaching and learning method was specified in the research paper. Meta-analysis of the research data where the teaching and learning method was designated displayed significances in CPS, PBL and Storytelling. Unlike the cognitive aspect, the analysis from the affective aspect showed that the effect size of the research data without the specified teaching and learning method was larger than those with specified teaching and learning method with a statistical significance. Meta-analysis of the data according to the teaching and learning method displayed no statistical significance. Based upon these research results, this study suggested implications for the effective programming education.

• KSTLE International Journal
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• v.2 no.1
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• Structural Engineering and Mechanics
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• v.31 no.6
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• pp.737-749
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• 2009

The problem of estimating the dynamic response of a distributed parameter system excited by a moving vehicle with random initial velocity and random vehicle body mass is investigated. By adopting the Galerkin's method and modal analysis, a set of approximate governing equations of motion possessing time-dependent uncertain coefficients and forcing function is obtained, and then the dynamic response of the coupled system can be calculated in deterministic sense. The statistical characteristics of the responses of the system are computed by using improved perturbation approach with respect to mean value. This method is simple and useful to gather the stochastic structural response due to the vehicle-passenger-bridge interaction. Furthermore, some of the statistical numerical results calculated from the perturbation technique are checked by Monte Carlo simulation.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2179-2184
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• 2008

The ride comfort is more important according to train speedup. Generally it is defined as the vehicle vibration. There are many studies on evaluation method of ride comfort for railway. But the ride comfort for Korean high speed train(HSR 350x) has been assessed by statistical method according to UIC 513R. In this paper, the ride indices, which are measured in the Korean high speed train, have been analyzed and reviewed by appling the statistical methodology such as t-test, variance analysis(ANOVA) and regression analysis.

• Journal of Sasang Constitutional Medicine
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• v.22 no.4
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• pp.49-55
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• 2010

1. Objectives The purpose of this study is to assess the statistical methods used in the Journal of Sasang Constitutional Medicine and to identify the types of errors in the statistical analysis. 2. Methods We have reviewed quantitative articles published in the Journal of Sasang Constitutional Medicine from 2000 to 2009. Except for the case report, a total of 505 articles was reviewed by year. We focused on the methods of statistics in these articles. We have analysed the number of thesis used the statistical methods, the number of the statistical methods, the types of the statistical methods, and the errors of the statistical methods with the object of 202 thesis used the statistical method. 3. Results 1. Of the 370 articles, 202 used inferential statistics. 2. The most dominant was the thesis with one type of the statistical method forming 61.9% (125 thesis) of the total. 3. The ANOVA was the statistic of choice overall (40.1%), followed by the t-test (35.6%). 4. By examining the errors of the statistical methods, there were 49 thesis with errors among 81 thesis using ANOVA, 25 thesis among 72 thesis using t-test, and 18 over 62 thesis using chi-squared test. 4. Conclusions We have found various mistakes or misuses in the applications of statistical methodologies in the articles published in the Journal of Sasang Constitutional Medicine. It is necessary to present the cases of inappropriate statistical methods in order to improve the quality of academic researches. So long as Sasang constitutional medicine uses the statistical methods, researchers should fully examine and be aware of the statistical methods which they wish to use through other research articles, and statistic publications.