• Education of Primary School Mathematics
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• v.25 no.4
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• pp.329-341
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• 2022

Data collection is crucial to the process of statistical problem solving since it influences the quality of statistical data. However, there is little instruction on data collection in the Korean mathematics curriculum. In this study, we examined how the data were collected and how the data collection method was taught in the Korean mathematics textbooks for 3rd and 4th grades. As a result, the data appeared in these textbooks were collected by using a variety of methods, including surveys, experiments, observations, and secondary data collections. There were not enough instructions on experiments and observations, compared to surveys and secondary data collection. Additionally, as each textbook works with a distinct contents while teaching data collection, it is expected that there would be variations in the levels that students learn in relation to data collection. Based on these findings, we draw some discussion points to determine how to improve the mathematics curriculum in order to effectively teach data collection in the elementary school.

• 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.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.211-224
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• 2004

Distributing information on the internet is common in our daily life. In the past, e-mail has been the primary choice of exchanging information, but instant messengers are gaining popularity abroad and domestically because of their immediate responses. Instant messaging has become the fastest growing communication technology in recent years. Instant messaging is effectively a chat room for two people. Users that have accounts with the same provider are able to send messages via computer in real time. Instant messaging has exploded into the business world as companies now utilize the technology for everything from interoffice communication to client/customer communication. In this paper, we propose a method of instant messenger system design for effective collaboration of statistical data collection.

• Proceedings of the KSRS Conference
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• v.2
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• pp.788-790
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• 2006

The algorithm of calculating NUC table, based on Image data collection, is based on two basic assumptions. These basic assumptions are as follow: one is the NUC is of a linear nature. The other is all pixel see the same statistical distribution for large number of lines. We generated NUC tables for a radiometric calibration & validation of KOMPSAT-2 using a dark cal. Data.

• The Mathematical Education
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• v.58 no.3
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• pp.459-481
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• 2019

This study aims to investigate students' statistical thinking through statistical processes in different instructional settings: Teacher-centered instruction vs. student-centered learning. We first developed instructional materials that allowed students to experience all the processes of statistics, including data collection, data analysis, data representation, and interpretation of the results. Using the instructional materials for four classes, we collected and analyzed the data from 57 seventh graders' discourse and artifacts from two different instructional settings using the analytic framework generated on the basis of literature review. The results showed that students felt difficulty particularly in the process of data collection and graph representations. In addition, even though data description has been heavily emphasized for data analysis in statistics education, it is surprisingly discovered that students had a hard time to understand the relationship between data and representations. Also, there were relationships between students' statistical thinking and instructional settings. Even though both groups of students showed difficulty in data collection and graph representations of the data, there were significant differences between the groups in terms of their performance. Whereas students from student-centered learning class outperformed in making decisions considering verification and justification, students from teacher-centered lecture class did better in problems requiring accuracy than the counterpart. The results from the study provide meaningful implications on developing curriculum and instructional methods for statistics education.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• Journal of the Korean School Mathematics Society
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• v.8 no.2
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• pp.167-181
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• 2005

Statistics is based on a data, therefore a practical use of suitable data is important in teaching statistics. But, most teachers feel always that there is seldom data that students can understand easily. In this study, we presented a teaching method of statistics education that can elevate student's participation and interest in their statistics class using a web-based data collection program and MS Excel software. Also, the presented teaching method may apply extending to various part of statistics education.

• Wind and Structures
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• v.2 no.3
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• pp.133-150
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• 1999

Significant costs to the public and private sectors due to recent extreme wind events have motivated the need for systematic post-hurricane damage data collection and analysis. Current post disaster data are collected by many different interested groups such as government agencies, voluntary disaster relief agencies, representatives of media companies, academicians and companies in the private sector. Each group has an interest in a particular type of data. However, members of each group collect data using different techniques. This disparity in data is not conducive to quantifying damage data and, therefore, inhibits the statistical and spatial description of damage and comparisons of damage among different extreme wind events. The data collection does not allow comparisons of data or results of analyses within a group and also prohibits comparison of damage data and information among different groups. Typically, analyses of data from a given event lead to different conclusion depending upon the definition of damage used by individual investigators and the type of data collected making it difficult for members of groups to compare the results of their analyses with a common language and basis. A formal method of data collection and analysis-within any single group-would allow comparisons to be made among different individuals, hazardous events and eventually among different groups, thus facilitating the management and reduction of damage due to future disaster. This research introduces a definition of damage to single family dwellings, and a common method of data collection and analysis suited for groups interested in regional characterization of damage. The current state-of-data is presented and a method for data collection is recommended based on these existing data collection methods. A fixed-scale damage index is proposed to consider the damage to a dwelling's feature. Finally, the damage index is applied to three dwellings damaged by Hurricane Iniki (1992). The damage index reflects the reduced functionality of a structure as a single family detached dwelling and provides a means to evaluate regional damage due to a single event or to compare damage due to events of different severity. Evaluation of the damage index and the data available support recommendation for future data collection efforts.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.133-144
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• 2009

This paper presents a method for constructing and using transliteration rules which are based on Phonics, an instructional method for speaking and writing English letters. Conventional approaches to automatic transliteration often focused on statistical methods. However, the construction or the collection of correct transliteration examples is always the bottleneck of the statistical transliteration model. Also, in practical domains where the collection of such data is very difficult, such as education and tourism, it is reasonable to build a system without much qualified data. Furthermore, compared with Korean orthography of borrowed foreign words, the proposed approach is much easier to construct, and can generate more refined rules. The experimentation result shows that the proposed approach can improve the performance of a statistical-based transliteration system.