• Journal of Hospice and Palliative Care
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• v.13 no.1
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• pp.1-6
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• 2010

The purpose of clinical trials is to find evidences for the effects of experimental new drugs or treatments on human. For the successful clinical trials, it is not sufficient to use statistics only for the analyses of collected data, but it is necessary to extend the usage of statistics in various ways. At the beginning of the study, one needs to use statistics for systematically and concretly planning the study. For this, we discussed the usage of statistics in defining the effect, determining the sample size, statistical analyses, and so on.

• Journal of the Korean School Mathematics Society
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• v.6 no.1
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• pp.45-63
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• 2003

This study is a research about the effect on achievement, retention and attitude of learning descriptive statistics with the computer software. For this study, 60 students are randomly divided two groups, one is an experimental group using software, the other one is a control group using lecture type of learning statistics. For the analysis, both groups are divided three subgroups according to mathematical ability. Also the topic "descriptive statistics" is divided by 5 subtopics. The test is divided three parts(computation, concept and application) according to knowledge type. The attitude toward statistics is investgated with questionaire and interview with both groups. The achievement test is taken after 8 class periods. The retention test were administered together six weeks after achievement test. The experimental group achieved significantly better than in concept type while the control group performed significantly better than the experimental group in computation type. With respect to the attitude toward statistics, lower ability students may have been negatively affected by the use of software.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5905-5926
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• 2017

Sentiments can profoundly affect individual behavior as well as decision-making. Confronted with the ever-increasing amount of review information available online, it is desirable to provide an effective sentiment model to both detect and organize the available information to improve understanding, and to present the information in a more constructive way for consumers. This study developed a unified phrase-based topic and sentiment detection model, combined with a tracking model using incremental hierarchical dirichlet allocation (PTSM_IHDP). This model was proposed to discover the evolutionary trend of topic-based sentiments from online reviews. PTSM_IHDP model firstly assumed that each review document has been composed by a series of independent phrases, which can be represented as both topic information and sentiment information. PTSM_IHDP model secondly depended on an improved time-dependency non-parametric Bayesian model, integrating incremental hierarchical dirichlet allocation, to estimate the optimal number of topics by incrementally building an up-to-date model. To evaluate the effectiveness of our model, we tested our model on a collected dataset, and compared the result with the predictions of traditional models. The results demonstrate the effectiveness and advantages of our model compared to several state-of-the-art methods.

• Research in Mathematical Education
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• v.17 no.4
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• pp.243-266
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• 2013

Accompanied with ongoing calls for reform in statistics curriculum, mathematics and statistics teachers purposefully have been reconsidering the curriculum and the content taught in statistics classes. Changes made are centered around statistical inference since teachers recognize that students struggle with understanding the ideas and concepts used in statistical reasoning. Despite the efforts to change the curriculum, studies are sparse on the topic of characterizing student learning and understanding of statistical inference. Moreover, there are no tools to evaluate students' statistical reasoning in a coherent way. In response to the need for a research instrument, in a series of research study, the researcher developed a reliable and valid measure to assess students' inferential reasoning in statistics (IRS). This paper describes processes of test blueprint development that has been conducted from review of the literature and expert reviews.

• Journal of Society of Preventive Korean Medicine
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• v.15 no.1
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• pp.17-27
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• 2011

Objective : The purpose of this study was to identify the trend of research in the Korean Journal of Oriental Preventive Medicine and to suggest future perspective for oriental preventive medicine research. Method : The contents of 344 articles published in this journal was reviewed from its beginning year 1997 to year 2010. Result : The number of articles was increased as times go on. An analysis of the research design showed, experimental research (in vivo or in vitro) was 36.9%, survey research was 26.5%, review was 20.1%. In the major classifications of topics published, health management 28.5%, oriental medicine effectiveness 25.3%, herbal safety and toxicity 13.1%, and environmental and occupational medicine 9.0% respectively. Conclusion : There has been a lack of health preservation(Yang-saeng) topic, epidemiology and health statistics topic. Further research need qualitative study and each subjects of oriental preventive medicine.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.231-237
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• 1997

The Koziol-Green(KG) model has become an important topic in industrial life testing. In this paper we suggest MLE of the reliability function for the Weibull distribution under the KG model. Futhermore, we compare Kaplan-Meier estimator, Nelson estimator, Cheng & Chang estimator, and Ebrahimi estimator with proposed estimator for the reliability function under the KG model.

• Korea Trade Review
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• v.46 no.4
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• pp.61-76
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• 2021

This study focuses on three logistics-related news (Logistics Newspaper, Korea Shipping Gadget, and Korea Shipping Newspaper) in order to present changes in logistics issues, centering on Corona 19, which has recently had the greatest impact in the world. For data collection, two-year news articles in 2019 and 2020 (title, article, content, date, article classification, article URL) were collected through web crawling (using Python's BeautifulSoup, requests module) on the homepages of three representative logistics-related media companies. As for the data analysis methods, fundamental statistical analysis, Latent Dirichlet Allocation (LDA) for topic modeling, and Scattertext were performed. The analysis results were as follows. First, among the three news media related to logistics, the Korea Shipping Newspaper was carrying out the most active media activities. Second, through topic modeling with LDA, eight logistics-related topics were identified, and keywords and significant issues of each topic were presented. Third, the keywords were visually expressed through Scattertext. This is the first study to present changes in the logistics field, focusing on articles from representative logistics-related media in 2019 and 2020. In particular, 2019 and 2020 can be divided into before and after the outbreak of Corona 19, which has had a great impact not only on the logistics field but also on our lives as a whole. For future work, a multi-faceted approach is required, such as comparative studies of logistics issues between countries or presenting implications based on long-term time-series articles.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.771-780
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• 2012

In the current analysis, we examine news coverage data widely used in media studies. News coverage data is usually time series data to capture the volume or the tone of the news media's coverage of a topic. We first describe the distributional properties of autoregressive conditionally heteroscadestic(ARCH) effects and compare two major American newspaper's coverage of U.S.-North Korea relations. Subsequently, we propose a change point detection model and apply it to the detection of major change points in the tone of American newspaper coverage of U.S.-North Korea relations.

• Journal of the Korean School Mathematics Society
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• v.25 no.1
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• pp.1-17
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• 2022

The goal of this study was to analyze students' views about statistical themes in Mongolian secondary schools in Ulaanbaatar. To this end, 129 9th grade students were stratified random sampling at two secondary schools in Ulaanbaatar, Mongolia, and a survey was conducted on them. The attitude survey focused on six factors contributing to the attitude: affective, cognitive competency, value, difficulty, interest, and student effort. The results show that students believed their statistical knowledge and skills have increased compared to the beginning of the courses. Furthermore, the survey revealed that they perceived statistics as neither an easy nor a difficult subject. Students' interest in statistics was neutral in general. These results suggest a need to develop effective and innovative statistical teaching and learning methods that can attract attention to statistical topics.