• Journal of the Korean School Mathematics Society
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• v.24 no.4
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• pp.349-367
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• 2021

In this study, 85 studies on probability education from 2000 to 2020 were analyzed by publishing year, journals, research subjects, and research topics. Especially, fundamental probabilistic ideas presented by Batanero et al.(2016) were applied to examine which topics were dominant in domestic probability education research. As a result, it was found that there has been a few research in probability education in Korea during the past 20 years, and the number of human subject studies was slightly more than the number of non-human subject studies. In addition, the analysis of research topics according to the fundamental probabilistic ideas showed that two topics, conditional probability and independence and combinatorial enumeration and counting, were dominant in domestic probability education research. However, while both conditional probability and independence and combinatorial enumeration and counting are introduced to young children using intuitive manners in international probability education research, subjects related to these topics were primarily high school students and pre and in-service teachers. Based on the results of this study, the implications for the goal and the direction of future probability education research were discussed.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.9-16
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• 2004

Recently, lattice conditional independence models(LCIMs) have been introduced for the analysis of non-monotone missing data patterns and of non-nested dependent regression models. This approach has been successfully applied to solve various problems in data pattern analysis, however, it suffers from computational burden to search LCIMs. In order to cope with this drawback, we propose a new scheme for finding LCIMs based on the essential graph. Also, we show that the class of LCIMs coincides with the class of all transitive acyclic directed graph(TADG) models which are Markov equivalent to a specific acyclic directed graph(ADG) models.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1081-1090
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• 2010

Most nations including Korean government make a great endeavor to realize low-carbon and green-growth world. We also work hard to expand bicycle facilities and bicycle road in order to increase bicycle transportation rate. Nowadays number of cyclists is increasing but fortunately, bicycle accidents also increase rapidly. Most data of bicycle accidents published by National Police Agency annually are represented as frequencies in two dimensional contingency tables. In this work, risk rates and characteristics of bicycle accidents are analyzed by using concepts of the probability and conditional probability. Especially with numbers of estimated cyclists and registered cars, risk rates of various kinds of bicycle accidents are obtained. Under the assumption of the conditional independence, probability of bicycle accident occurred at realistic situations could be estimated. Furthermore we discuss to reduce bicycle accidents with these results obtained in this work.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.768-777
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• 2006

The purpose of this study lies in formulating the landscape preference model using a conditional logit that involves the effect of visual elements as well as landscape itself on landscape preferences. To measure landscape preferences, a photo-questionnaire composed of paired photographs of the Cairngorms National Park of Scotland and the Jirisan National Park of Korea was distributed to visitors to the Jirisan National Park of Korea. Visual elements of landscape quantitatively measured by photogrammetry were reduced to orthogonal principal components that were subsequently used as explanatory variables in a conditional logit. As a result, the mixed conditional logit including the effect of landscape itself satisfied the Independence of Irrelevant Alternatives (IIA) property and showed reliable goodness of fit (${\rho}^2=0.25$). It was concluded that the mixed conditional logit including the effect of landscape itself was appropriate for landscape preference model rather than usual conditional logit excluding the effect.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.337-346
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• 2004

The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1421-1428
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• 2013

In this paper, we would like to test whether the hit at a particular bat has a dependency with the hitting results at the previous bats in professional baseball games. For this purpose, we used the 2011 Korean Baseball League data. We find out that the hitting percentage at a particular bat has no dependency with the hit at the previous bat, after reviewing the conditional probability of hit at each bat and the lift. From the independence test of hits at consecutive bats, and hit at a particular bat with no hits at previous bats, we can conclude that hits at particular bats are not dependent on the hits at previous bats in most cases. Hence, we can safely conclude that a hit at a particular bat is statistically independent from the hits at the previous bats.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.479-496
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• 2003

We investigate logit confidence intervals for the odds ratio based on the delta method. These intervals are constructed using pseudo-Bayes estimators. The Gart method and Agresti method smooth the observed counts toward the model of equiprobability and independence, respectively. We obtain better coverage probability by smoothing the observed counts toward the pseudo-Bayes estimators in 2$\times$2 table. We also improve legit confidence intervals in 2$\times$2$\times$K tables by generalizing these ideas. Utilizing pseudo-Bayes estimators, we obtain better coverage probability by smoothing the observed counts toward the conditional independence model, no three-factor interaction model and saturated model in 2$\times$2$\times$K tables.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.713-716
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• 2005

In this paper, in order to identify and recognize attack patterns, we propose a Bayesian classification using frequent patterns. In theory, Bayesian classifiers guarantee the minimum error rate compared to all other classifiers. However, in practice this is not always the case owing to inaccuracies in the unrealistic assumption{ class conditional independence) made for its use. Our method addresses the problem of attribute dependence by discovering frequent patterns. It generates frequent patterns using an efficient FP-growth approach. Since the volume of patterns produced can be large, we propose a pruning technique for selection only interesting patterns. Also, this method estimates the probability of a new case using different product approximations, where each product approximation assumes different independence of the attributes. Our experiments show that the proposed classifier achieves higher accuracy and is more efficient than other classifiers.

• Management & Information Systems Review
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• v.38 no.3
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• pp.35-53
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• 2019

A standing auditor can perform the monitoring and control activities for the opportunistic behaviors of top manager. However, for this purpose she/he must have the independence from top manager. Thus, this study is designed to analyze the factors that influences the independence of standing auditor. The independence of standing auditor as dependent variable was measured in terms of school and company ties to top manager. The relationship between the shareholding of professional top manager and independence of standing auditor, and the moderating effects of the shareholdings of related-party, institutional investors, and foreign investors were examined by implementing multiple regression and conditional moderating effect analyses. The findings present a negative relationship between the shareholding of professional top managers and the independence of standing auditor. They also reveal a positive moderating effect of the shareholding of related-party on that relationship. On the other hand, the shareholdings of foreign and institutional investors did not significant change the relationship between the shareholding of professional top manager and the independence of standing auditor. The findings imply that professional manager might be able to lower the controlling mechanism by appointing a standing auditor having low independence. Related-party as an internal control mechanism might be beneficial to reduce this effect while institutional investors or foreign investors as an external control mechanisms might not. This is the first study that examine the antecedents of the independence of standing auditor in terms of the characteristics of ownership structure. It provides a guideline for selecting an effective standing auditor with the consideration for ownership structure.