• Communications of Mathematical Education
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• 제36권4호
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• pp.535-558
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• 2022

In the current society, where statistical literacy is recognized as an important ability, statistical education utilizing the statistical problem solving, a series of processes for performing statistics, is required. The result interpretation stage is especially important because many forms of statistics we encounter in our daily lives are the information from the analysis results. In this study, data on private education were provided to pre-service mathematics teachers, and a project was carried out in which they could experience a statistical problem solving process using the population mean estimation. Therefore, this study analyzed the characteristics shown by pre-service mathematics teachers during the result interpretation stage. First, many pre-service mathematics teachers interpreted results based on the data, but the inference was found to be a level of 2 which is not reasonable. Second, pre-service mathematics teachers in this study made various kinds of decisions related to public education, such as improving classes and after-school classes. In addition, the pre-service mathematics teachers in this study seem to have made decisions based on statistical analysis results, but they made general decisions that teachers could make, rather than specifically. Third, the pre-service mathematics teachers of this study were reflective about the question formulation stage, organizing & reducing data stage, and the result interpretation stage, but no one was reflective about the result interpretation stage.

• Journal of Intelligence and Information Systems
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• 제18권4호
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Strategy21
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• 통권34호
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• pp.207-235
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• 2014

이 논문의 목적은 해군력 개량화를 소개하고 그 활용에 대하여 제안함에 있다. 어떻게 하면 여러 국가 간의 다양한 분쟁에 대한 해군력의 효과를 효과적으로 이해할 수 있을까? 혹은, 어떻게 하면 다양한 해군력의 나라별, 시간별 변화를 이해를 할 수 있을까? 지금까지 많은 학자들이 해군력의 변화와 그 변화에 따른 해군력이 분쟁에 미치는 영향을 규명하려고 많은 노력을 해왔다. 그 중의 한 방법이 정성적인 방법이나 아직 정량적인 시도는 매우 적다. 이 글은 해군력을 정량화하는 방법과 그 데이터를 이용하여 여러 기존 이론을 검증하고 여러 다른 연구주제를 연구하는데 어떻게 이용이 될 것인지를 소개를 하는 글이다. 본 논문의 주요 쟁점은 다음과 같다. 첫째, 계량화적 접근이란 무엇인가에 대해 논의 해 본다. 계량화란 무엇이며 정성적인 방법과의 차이는 무엇인지를 통해 정량화의 이용 가치에 대해 논의해 본다. 둘째, 해군력의 정량화이다. 해군력의 정량화를 위해 어떠한 기준들을 세우고, 그 기준에 따라 함정들을 코딩하고 톤수를 세는 과정을 설명한다. 셋째, 정량화된 해군력을 바탕으로 동북아시아 국가들의 해군력 변화를 서술적으로 분석한다. 이제 주어진 해군력 데이터(주요 함정의 톤수)를 가지고 각 동북아 국가별 시간별로 어떠한 변화를 거처 왔고, 각 분쟁들 (1,2차 세계대전 등)에는 어떠한 상관관계가 있는지를 단순통계적 방법을 이용하여 알아본다. 넷째, 해군력의 변화가 경쟁국가 간의 전쟁 발발에 있어서 어떤 영향을 미치는 지에 대하여 통계적인 방법을 이용하여 검증해 본다. 묘사적인 방법은 다른 요소들에 대한 통제가 이루어 지지 않아, 정확히 해군력과 경쟁국가 간의 전쟁에 대한 인과적인 관계를 증명하기에는 한계가 있다. 따라서, 다른 경쟁적 이론들을 (예를 들어 민주평화론 등) 통제하여 해군력이 숙적국가 간의 전쟁 발발에 미치는 영향을 검증하였다. 상호 해군력의 증가는 경쟁국가 간에는 전쟁을 덜 일으키는 요인으로 작용하였으며, 이는 해군력이 경쟁국가 간에는 억제력이 있다고 추론 할 수 있다. 궁극적으로 해군력의 영향에 대한 정량적인 접근은 기존 연구의 검증, 미래 예측, 국가의 정책결정자들에게 보다 신뢰가 가는 자료를 제공하는 장점들이 있다. 이러한 장점들을 바탕으로 해군력의 영향에 대한 연구는 분쟁분야에 있어서 학술적이나 실용적인 측면에서 많은 이점이 있다.

• School Mathematics
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• 제13권3호
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• pp.363-384
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• 2011

This study is based on the recognition that the school mathematics education should reinforce the heuristic and constructional aspects related with discoveries of mathematical rules and understanding of mathematical concepts from real world situations as well as the deductive and formal aspects emphasizing on mathematical contents precisely. The 11th grade students of one class from a city high school with average were chosen. They were given time to learn various functions of Excel in regular classes of "Information Society and Computer" subject. They don't have difficulty using cells, mathematical functions and statistical functions in spreadsheet. Experiment was performed for six weeks and there were two hours of classes in a week. Considering the results of this research, teaching materials using spreadsheets play an important role in helping students to experience probabilistic and statistical reasoning and construct mathematical thinking. This implies that teaching materials using spreadsheet provide students with an opportunity to interact with probabilistic and statistical situations by adopting engineering which can encourage students to observe and experience various aspects of real world in authentic situations.

• Journal of the Korean Data and Information Science Society
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• 제5권2호
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• pp.75-85
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• 1994

In this paper, I introduce the goodness-of-fit test statistics for exponential distribution using accelerated life test data. The ALT lifetime data were obtained by assuming step-stress ALT model, specially TRV model introduced by DeGroot and Goel(1979). The critical values are obtained for proposed test statistics, Kolmogorov-Smirnov, Kuiper, Watson, Cramer-von Mises, Anderson-Darling type, under various sample sizes and significance levels. The powers of the five test statistic are compared through Monte-Cairo simulation technique.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.37-46
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• 1996

In this paper, we introduce the goodness of fit test procedure for lifetime distribution using step stress accelerated lifetime data. Using the nonpapametric estimate of acceleration factor, we prove the strong consistence of empirical distribution function under null hypothesis. The critical vailues of Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises statistics are computed when the lifetime distibution is assumed to be exponential and Weibull. The power of test statistics are compared through Monte-Cairo simulation study.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.475-480
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• 2007

대화관리시스템은 사용자 발화로부터 사용자의 의도를 추론하여 시스템의 응답을 결정하고 이를 사용자에게 자연스러운 형태로 반환하는 역할을 한다. 본 논문에서는 마르코프 의사 결정과정에 기반한 대화관리자를 통하여 정확한 동작 수행과 사용자의 자연스러운 발화를 가능케 하는 대화관리시스템에 대해서 소개한다. 마르코프 의사 결정과정 대화관리자는 실세계 환경을 모델링 하는 유한 개수의 상태들과 이를 이용한 통계적 학습을 통해 시스템 응답을 결정 한다. 본 대화관리시스템은 대화관리자 이외에 언어이해부, 영역규칙 적용부, 목적시스템 제어부, 예제기반 응답생성부로 이루어져 있으며, 각 구성요소는 영역이식에 용이하도록 설계되어 있다.

• Communications of Mathematical Education
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• 제14권
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• pp.273-295
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• 2001

통계는 연역적 사고를 강조하는 수학의 다른 영역과 달리 귀납적 추론과 직관적 사고를 요구한다. 따라서 학교 수업에서 학생들이 실제적인 상황을 모델링 할 수 있도록 하며, 주어진 상황에서 자료를 올바르게 산출하고 분석 할 수 있도록 적절한 지도 방법이 필요하다. 그렇지만 학교 수업은 대다수 알고리즘 연습 위주의 통계 학습-지도로 통계적 사고 교육이 제대로 이루어지지 못하고 있다. 이로 인해 학생들은 형식적인 통계 처리에는 익숙하지만 통계 교육의 궁극적 목적인 변이성과 자료를 현명하게 다루는 능력이 부족하다. 본고에서는 피상적인 기계적 계산위주의 통계교육에서 실제적인 자료를 수집하고, 이를 적절히 가공 처리하여 정보의 가치를 높일 수 있는 통계 지도 방향을 탐색해 보고자 한다.

• The Korean Journal of Applied Statistics
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• 제17권1호
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• pp.145-151
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• 2004

PROC MIXED fits a variety of mixed models to data and enables one to use these fitted models to make statistical inferences about the data. However, the simulation study in this article shows that PROC MIXED using REML estimators provides one with a confidence interval, that does not keep the stated confidence coefficients, on sums of two variance components in the simple regression model with unbalanced nested error structure which is a mixed model.

• Journal of Korean Society for Quality Management
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• 제36권1호
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• pp.1-6
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• 2008

The purpose of stability study of pharmaceutical products is to establish the shelf life based on the change of the quality with time. Stability study generally consists of a random sample of dosage units from a batch or several batches placed in a storage room and periodically assayed for their drug content. The statistical methods of assessing the shelf-life of drug in the market is considered with the current KFDA regulations. An illustrated application to some stability data from the pharmaceutical industry is also presented with the discussion.