• International Journal of Reliability and Applications
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• v.8 no.2
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• pp.153-173
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• 2007

Wood-plastic composites (WPC) are gaining market share in the building industry because of durability/maintenance advantages of WPC over traditional wood products and because of the removal of chromated copper arsenate (CCA) pressure-treated wood from the market. In order to ensure continued market share growth, WPC manufacturers need greater focus on reliability, quality, and cost. The reliability methods outlined in this paper can be used to improve the quality of WPC and lower manufacturing costs by reducing raw material inputs and minimizing WPC waste. Statistical methods are described for analyzing stiffness (tangent modulus of elasticity: MOE) and flexural strength (modulus of rupture: MOR) test results on sampled WPC panels. Descriptive statistics, graphs, and reliability plots from these test data are presented and interpreted. Sources of variability in the MOE and MOR of WPC are suggested. The methods outlined may directly benefit WPC manufacturers through a better understanding of strength and stiffness measures, which can lead to process improvements and, ultimately, a superior WPC product with improved reliability, thereby creating greater customer satisfaction.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.345-354
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• 2016

Inhomogeneous Poisson process models are widely applied to landslide data to understand how environmental variables systematically influence the risk of landslides. However, those models cannot successfully explain the clustering phenomenon of landslide locations. In order to overcome this limitation, we propose to use a Cauchy cluster process model and show how it improves the goodness of fit to the landslide data in terms of K-function. In addition, a numerical study is performed to select the optimal estimation method for the Cauchy cluster process.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.77-91
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• 2022

The optimal threshold estimation is considered in order to discriminate the mixture distribution in the fields of Biostatistics and credit evaluation. There exists well-known various accuracy measures that examine the discriminant power. Recently, Matthews correlation coefficient and the F1 statistic were studied to estimate optimal thresholds. In this study, we explore whether these accuracy measures are appropriate for the optimal threshold to discriminate the mixture distribution. It is found that some accuracy measures that depend on the sample size are not appropriate when two sample sizes are much different. Moreover, an alternative method for finding the optimal threshold is proposed using the correlation coefficient that defines the ratio of the confusion matrix, and the usefulness and utility of this method are also discusses.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.286-287
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• 2023

The function of Aids to Navigation(AtoN) must be sustainable. In order to provide sustainable services, it is necessary to prevent repeated AtoN accidents through accurate data analysis and to perform maintenance to maintain functions. What is needed for this is the AtoN status statistics service. AtoN Status Statistics Service is a service that extracts existing data in gml format and extracts and processes it in the period, type, and format desired by the manager.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.47-59
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• 2020

In this paper, we present the longitudinal Markov binary regression model with t-link function when its transition order is known or unknown. It is assumed that logit or probit models are considered in binary regression models. Here, t-link function can be used for more flexibility instead of the probit model since the t distribution approaches to normal distribution as the degree of freedom goes to infinity. A Markov regression model is considered because of the longitudinal data of each individual data set. We propose Bayesian method to determine the transition order of Markov regression model. In particular, we use the deviance information criterion (DIC) (Spiegelhalter et al., 2002) of possible models in order to determine the transition order of the Markov binary regression model if the transition order is known; however, we compute and compare their posterior probabilities if unknown. In order to overcome the complicated Bayesian computation, our proposed model is reconstructed by the ideas of Albert and Chib (1993), Kuo and Mallick (1998), and Erkanli et al. (2001). Our proposed method is applied to the simulated data and real data examined by Sommer et al. (1984). Markov chain Monte Carlo methods to determine the optimal model are used assuming that the transition order of the Markov regression model are known or unknown. Gelman and Rubin's method (1992) is also employed to check the convergence of the Metropolis Hastings algorithm.

• Korea journal of population studies
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• v.12 no.1
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• pp.19-29
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• 1989

It is well known that vital statistics is of great importance as basic data for establishing various range of national policies. Especially, vital statistics is important among demographic information for monitoring and evaluating the population policy, for constructing life table, for making population projection, and for studying various aspects of the society. In principle, the production of vital statistics is based on the registration system. It is, however, still observed that there are some limitations in utilizing fully the registration system due to the inherent problems such as problems in its coverage, accuracies and timeliness. Thus, as an alternative, many countries conduct survey on vital statistics in order to supplement the registration system and obtain in-depth data. Korea is no exception in this aspect. The National Bureau of Statistics carries out the so-called Continuous Demographic Survey. This is a kind of multi-round retrospective survey, covering 32, 000 households and having reference period of one month. The survey has also characteristics of multi-subject sample. Thus, surveys on economic activity status of population, house-hold income & expenditure, and social indicators are together conducted with the same sample. It is, however, found that the survey itself tends to have some quality problems. Especially, the quality problems connected with field data collection are summarized as coverage error, non-response error and response error. Although it is inevitable not to be free from these errors, we should make all our efforts to reduce the errors. The probable schemes pointed out in this paper are as follows : 1) the strengthening formal quality control activities, 2) the review of the survey method, i. e., the combining interview method with mail-sending and mail-back method or pick-up method, 3) well documentation for various cases found in every stage of data collection, and 4) the strengthening the analytical activities. It is, also, emphasized that sincerity of planners and interviewers is the most important factor among other things.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.653-665
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• 2009

All the policies and plans need to be carried out at the proper times in order that they would work properly for what they are made for. It is will known that statistics are one of the most useful tools in deciding the proper times for the policies. In this paper we show how to use statistics in evaluating the policies already carried with respect to the time when they were executed in dealing with the population policy we had in 1983 when the total fertility rate hit the population replacement level 2.1. Two methods have been tried to show that the policy carried in 1983 missed the proper changing time. The one is to make forecasting only with the data possible before 1982 and show how close they can be to the real situation of today. The other is to show what would happen if the policies aiming to suppress population growth had been changed or abandoned. Both results from two methods give some quantified information about the population policy of 1983. Especially the prediction tells that we could have forecasted the problem of low fertility of this century in 1983.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.651-660
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• 2011

This study aims at improving teaching and learning abilities on the courses of probability/statistics in the fields of the S/W and H/W. In order to do this, this paper firstly conducts a survey which measures the perception of the surveyees' necessity of the related courses, and includes the contents that the related courses should cover. Secondly, this paper analyzes the educational effect on the achievement by studying Pattern Recognition, a major course of S/W and H/W, with combining probability/statistics or data analysis. Lastly, this paper suggests the promising pedagogical method for educating probability/statistics by using a survey and the case studies. In this way, this paper shows the necessity of probability/statistics for acquiring a new technology and the flexible approach of various subjects.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.887-898
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• 2016

The purpose of this study is to improve the learning ability of probability/statistics for H/W majors. Firstly, we developed a teaching method coupling probability/statistics with programming and multimedia signal processing courses that are opened in the H/W major curriculum. By use of its teaching-learning, we tried to verify the effectiveness on the improvement of learner's academic achievement and then analyze its educational efficiency through the regression analysis. Secondly, by analyzing the surveys and the statistical results of the education cases, we proposed a management plan on efficient teaching-learning in order to cultivate the learning ability of probability/statistics at a future time. Lastly, we concluded that probability/statistics is a required course of learners so as to contribute for the advanced technical development and the enhanced competitiveness in the field of the H/W.

• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).