• Journal of Family Resource Management and Policy Review
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• v.6 no.1
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• pp.35-51
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• 2002

This study is the basic step of including the economical value of household labor into the existing GDP. Therefore this study analyzes statistical data; $\mathbb{\ulcorner}$Economical Active Population Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Time Used Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Basic Wage Structural Survey$\mathbb{\lrcorner}$, and $\mathbb{\ulcorner}$City Household Survey$\mathbb{\lrcorner}$ for that step and will help people to reconsider the importance of the economical value household work. Economical Active Population Survey classifies housework as economically nonoproductive activity Time Use Survey does not have an clear classification for action. Basic Wage Structural Survey must give subdividable information on wage. City Household Survey should include more details and more data of household durables.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.29-39
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• 1998

The Farm Household Economy Survey (FHES) is carried out by the Ministry of Agriculture and Forestry every year. In this paper, we reveiwed the current status of the FHES and assessed the precision of the survey results. Finally we proposed some recommendations for improving the precision and presented the improvable directions of FHES with some feasible solutions.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.55-66
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• 2010

Propensity score adjustment(PSA) has been suggested as approach to adjustment for volunteer internet survey. PSA attempts to decrease the biases arising from noncoverage and nonprobability sampling in volunteer panel internet surveys. Although PSA is an appealing method, its application for internet survey regarding Korea presidential election and its effectiveness is not well investigated. In this study, we compare the Ni Korea internet survey with the telephone survey conducted by MBMR and KBS for 2007 Korean presidential election. The result of study show that the accuracy of internet survey can be improved by using PSA. And it is critical to include covariates that highly related to the voting tendency and the role of nondemographic variables seems important to improving PSA for Korea presidential election prediction.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1196-1213
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• 2020

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.197-211
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• 2004

According to the increase of internet application, the marketing process as well as the research and survey, the education process, and administration of government are very depended on web bases. All kinds of goods and sales which are traded on the internet shopping malls are extremely increased. So, the necessity of automatically intelligent information system is shown, this system manages web site connected users for effective marketing. For the recommendation system which can offer a fit information from numerous web contents to user, we propose an automatic recommendation system which furnish necessary information to connected web user using statistical learning theory and bayesian fuzzy clustering. This system is called collaborative CRM in this paper. The performance of proposed system is compared with the other methods using real data of the existent shopping mall site. This paper shows that the predictive accuracy of the proposed system is improved by comparison with others.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.443-452
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• 1993

A check list which includes the items that are to be considered in the process of the statistical data collection and analysis by non-scientific organizations is proposed. Based on the suggested check list, the output resulting from the statistical survey conducted by private organizations, banks, organs of expression and enterprises in Gwangju and Chonnam are examined about the validity of data collection and statistical analysis.

• Research in Mathematical Education
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• v.26 no.3
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• pp.127-146
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• 2023

Statistical thinking has a broad definition but focuses on the context of regression modelling in the present study. To foster students' statistical thinking within the context, teaching should no longer be seen as transfer of knowledge from teacher to students but as a process of engaging with learning activities in which they develop ownership of knowledge. This study aims at collaborative learning contexts; students were divided into small groups in order to increase opportunities for peer collaboration. Each group of students was asked to do a regression project after class. Through doing the project, they learnt to organize and connect previously accrued piecemeal statistical knowledge in an integrated manner. They could also clarify misunderstandings and solve problems through verbal exchanges among themselves. They gave a clear and lucid account of the model they had built and showed collaborative interactions when presenting their projects in front of class. A survey was conducted to solicit their feedback on how peer collaboration would facilitate learning of statistics. Almost all students found their interaction with their peers productive; they focused on the development of statistical thinking with concerted effort.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.281-282
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• 2021

The construction industry is known for a large number of workers and its high employment inducing effect. Therefore, the survey on the wages of the construction industry is an important basic data for grasping fluctuations according to the survey cycle and establishing future policies, and it is a statistical data having a large impact on related industries. In this study, we intend to conduct a comparative analysis of 'the wage survey in Construction sector,' which is the representative nationally approved statistics that surveys the current construction industry wages, and 'the labor force survey of business establishment'.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.437-447
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• 2009

Recently, in addition to analyzing data with appropriate statistical methods, statistical analysts in the industrial fields face difficulties that they have to compose proper datasets for analysis objectives via extracting or generating processes from diverse data storage devices. In this paper we survey and compare many state-of-the-art data access technologies adopted by several commonly used statistical packages. More understanding of these technologies will help to reduce the costs occurring when analyzing large size of datasets in especially data mining works, and so to allow more time in applying statistical analysis methods.

• Korean Journal of Community Nutrition
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• v.24 no.1
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• pp.60-76
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• 2019

Objectives: The purpose of this study was to develop a systematic and standardized "The Survey on School Foodservice Program" that can identify the current status of school meals on the nationwide level. Methods: This study was carried out in six steps of the analysis of report/investigation data related to school foodservice in metropolitan and provincial offices of education, analysis of preceding research related to the actual status of school foodservice, field verification of the actual condition of the school foodservice site, development of a draft of "The Survey on School Foodservice Program", pilot study of a draft of "The Survey on School Foodservice Program", and suggestions of a final model of "The Survey on School Foodservice Program" from August to December, 2017. Statistical analysis was performed for frequency analysis and descriptive analysis using the SPSS program ver. 23. Results: A draft of "The Survey on School Foodservice Program" was developed by analyzing the current status of report/research data on school meals in metropolitan and provincial offices of education, analyzing the preceding research on school meals, and identifying the actual conditions at school foodservice sites. To verify the validity of the school foodservice survey questionnaire, 1,031 schools were sampled from a total of 10,251 schools and the pilot test of '2017 School Foodservice Survey' was conducted. The final model of "The Survey on School Foodservice Program" consisted of 12 survey sections, 29 survey categories, and 433 survey items, and the survey cycle was set for one year and three years for each survey item. Conclusions: Based on the objective statistical data through "The Survey on School Foodservice Program", it is possible to develop the school foodservice policy, which will help establish the reliability of the school meals.