• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.231-236
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• 2021

The purpose and hypothesis of the article was the need to solve the following research tasks: Analysis of psychological and pedagogical literature on the research problem. To identify and experimentally test the effectiveness of organizational and pedagogical conditions affecting the creative self-development of a distance learning student. Research methods: analysis of philosophical and psychological-pedagogical literature on the problem under study; pedagogical experiment; modeling, questioning, testing, analysis of the products of students' creative activity (essays, creative works, creative projects) and the implementation of educational tasks, conversations, observations.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.341-353
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• 2008

The bootstrap method for the score test statistic is proposed in a bivariate negative binomial distribution. The Monte Carlo study shows that the score test for testing overdispersion underestimates the nominal significance level, while the score test for "intrinsic correlation" overestimates the nominal one. To overcome this problem, we propose a bootstrap method for the score test. We find that bootstrap methods keep the significance level close to the nominal significance level for testing the hypothesis. An empirical example is provided to illustrate the results.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.743-752
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• 2004

In this paper, we develop the Bayesian model selection procedure using the reference prior for comparing two nested model such as the independent and intraclass models using the distance or divergence between the two as the basis of comparison. A suitable criterion for this is the power divergence measure as introduced by Cressie and Read(1984). Such a measure includes the Kullback -Liebler divergence measures and the Hellinger divergence measure as special cases. For this problem, the power divergence measure turns out to be a function solely of $\rho$, the intraclass correlation coefficient. Also, this function is convex, and the minimum is attained at $\rho=0$. We use reference prior for $\rho$. Due to the duality between hypothesis tests and set estimation, the hypothesis testing problem can also be solved by solving a corresponding set estimation problem. The present paper develops Bayesian method based on the Kullback-Liebler and Hellinger divergence measures, rejecting $H_0:\rho=0$ when the specified divergence measure exceeds some number d. This number d is so chosen that the resulting credible interval for the divergence measure has specified coverage probability $1-{\alpha}$. The length of such an interval is compared with the equal two-tailed credible interval and the HPD credible interval for $\rho$ with the same coverage probability which can also be inverted into acceptance regions of $H_0:\rho=0$. Example is considered where the HPD interval based on the one-at- a-time reference prior turns out to be the shortest credible interval having the same coverage probability.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.25-33
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• 2015

From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.130-141
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• 2017

This study examined the effects of learners' job competency development on their vocational key competency improvement in lifelong education based on national competency standards. A survey was empirically carried out to 480 learners of lifelong education institutions in Seoul and the results were statistically analyzed. Covariance analysis was conducted to allow for external influences of lifelong education learners' educational environment in the process that verifies the effects of job competency development on vocational key competencies classified into 4 units, namely, mathematical skill, problem-solving skill, resource management skill, and communication skill. The findings are summarized as follows. First, all factors of job competency development had no effect on mathematical competency in the single dimension. Second, the testing of hypothesis 2 showed that education system(F=3.021, p<.05) and curriculum(F=6.684, p<.05) of job competency development factors had a significant positive effect on mathematical competency in the single dimension. Third, the testing of hypothesis 3 showed that only curriculum(F=5.865, p<.05) of job competency development factors had a significant positive effect on resource management in the single dimension. Fourth, the testing of hypothesis 4 showed that all factors of job competency development had no effect on communication in the single dimension. These findings suggest that the proper harmony of both education system and curriculum or all education system, curriculum and evaluation management in the combination of lifelong education support with teaching interaction can have a positive effect on the improvement of communication.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.285-292
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• 2017

This paper describes a recursive least-squares based convergent algorithm for driving characteristic classification for personalized autonomous driving. Recently, various researches on autonomous driving technology have been conducted for level 4 fully autonomous driving. In order for commercialization of the autonomous vehicle, personalized autonomous driving is required to minimize passenger's insecureness to the autonomous vehicle. To address this problem. this study proposes mathematical model that represents driving characteristics and recursive least-squares based algorithm that can estimate the defined characteristics. The actual data of two drivers has been used to derive driving characteristics and the hypothesis testing method has been used to classify two drivers. It is shown that the proposed algorithms can derive driving characteristics and classify two drivers reasonably.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.709-717
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• 2008

The difference of two one-sided kernel estimators is usually used to detect the location of the discontinuity points of regression function. The large absolute value of the statistic imply discontinuity of regression function, so we may use the difference of two one-sided kernel estimators as the test statistic for testing null hypothesis of a smooth regression function. The problem is, however, we only know the asymptotic distribution of the test statistic under $H_0$ and we hardly expect the good performance of test if we rely solely on the asymptotic distribution for determining the critical points. In this paper, we show that if we adjust the bias of test statistic properly, the asymptotic rules hold for even small sample size situation.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.503-515
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• 1998

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector, it follows approximately Poisson distribution. Under the four assumptions in the presence of errors and uncertainties for the Poisson parameters, an exact probability distribution of neutral particles have been derived. The probability distribution for the neutron signals received by a detector averaged over the three sources of errors is expressed as a four-dimensional integral of certain data. Two of the four integrals can be evaluated analytically and thereby the integral is reduced to a two-dimensional integral. The monotone likelihood ratio(MLR) property of the distribution is proved by using the Cauchy mean value theorem for the univariate distribution and multivariate distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem related to the distribution.

• Journal of Preventive Medicine and Public Health
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• v.15 no.1
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• pp.179-186
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• 1982

The methods controlling the confounding factors were discussed using the data of secondary infertility with induced abortion. Mantel-Haenszel method and logistic model were applied in the analysis to find out which factors were confounding and/or effect modification variables. In the logistic analysis, the main effect of induced abortion, spontaneous abortion, age and interaction effect between induced abortion and spontaneous abortion were chosen as independent variables being regressed into logistic functions. Spontaneons abortion was interpreted as a potential confounder and at the same time potential effect modifier and age was interpreted as potential confounder. Spontaneous abortion was shown to be more important influencing factor than age to the secondary infertility. In the course of logistic analysis, the problem of parameter estimation and hypothesis testing, assessing the fitness of a model, and selection of the best model were briefly explained. For the program of logistic model, FUNCAT Procedure of SAS package was chosen.

• Korean Journal of Psychosomatic Medicine
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• v.3 no.1
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• pp.64-71
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• 1995

Cognitive-behavioral approach can be clinically applied to coping with stress, because cognitions are playing a central mediating role in the occurances of stress and stress reactions. In other words, cognitive distortions can be associated with causing and/or maintaining psychopathology. The goal of cognitive-behavioral approach is to help the patients identify and alter cognitive distortions and maladaptive assumptions. This approach is aimed not at curing but rather at helping the patients to develop better coping strategies to deal with their life and work. The cognitive-behavioral techniques often used in this approach include problem solving, hypothesis-testing, self-monitoring, cognitive challenges, generating alternatives to automatic cognitive distortions, self-instruction, attribution and reattribution, and techniques to control or suppress thoughts. This approach is considered to be helpful for treatment and prevention of psychiatric disorders including psychosomatic disorders, in which stress can greatly affect their onset and course.