• Journal of Information Technology Services
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• v.23 no.3
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• pp.55-63
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• 2024

To grasp the structure of an industry and monitor its changes, it is essential to utilize relevant statistics. Various statistics are being compiled regarding the software (SW) industry, presenting diverse numerical values. However, without a precise understanding of the scope and measurement methods inherent to each statistic, gaining a rigorous understanding of the industry's structure and evolving trends becomes challenging. Moreover, significant discrepancies between similar statistics often lead to confusion among users. In the software (SW) industry, key statistics commonly used include SW production value and SW market size. As of 2022, the annual domestic SW production value is reported as 77.4 trillion KRW (based on ICT Survey), while the SW market size for the same year is stated as 38.5 trillion KRW (according to IDC data). Although production value and market size may seem conceptually similar, there is approximately a twofold difference between the figures provided. Without understanding the meanings of each statistic and the differences between them, there are limitations in utilizing these statistics effectively. While statistics are utilized for various purposes such as policy development or causal analysis of policy using statistical raw data, research that presents and analyzes the precise meanings and limitations of each SW-related statistic is virtually non-existent. Thus, this study aims to compare and analyze the methodologies and differences among key statistics used to represent the SW industry: SW production value, SW market size, and SW GDP statistics. Through this analysis, the goal is to contribute to a better understanding of the SW industry's structure and enable more accurate and rigorous utilization of relevant statistics.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.184-197
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• 1995

An objective and one-step detection procedure of multiple outliers is suggested by using the gaps of the order statistics. The detection procedure can be used as a routine outlier detection method of a statistical analysis computer program. The procedure is applied to some examples including the data selected by Kitagawa.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.167-180
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• 2006

The statistical survey and analysis is much restricted to time, space and material. The statistical survey and analysis could hardly resume. The statistical survey and analysis is very important to create various and accurate information. The statistical survey and analysis which is not a expert knowledge have many problems in productivity of information, reliability and etc. In this paper, we study the design and Implementation of web-based statistical survey and analysis consulting system which a client meet easily a statistical expert on the web.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.199-205
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• 2005

In general, simple correspondence analysis has handled mainly correspondence relations between the row and column categories but can not display the trends of their change over the time. For solving this problem, we will propose DSCA(Dynamic Simple Correspondence Analysis) of transition matrix data using supplementary categories in this study, Moreover, DSCA provides its trend of the change for the future by predicting and displaying trend toward the change from a standard point of time to the next.

• Journal of the Korean Statistical Society
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• v.34 no.3
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• pp.173-183
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• 2005

The Box-Cox power transformation is generally used for variance stabilization. Recently, Shin and Kang (2001) showed, under the Box-Cox transformation, invariant properties to the original model under the large mean and relatively small variance assumptions in time series analysis. In this paper we obtain some invariant properties in spatial statistics. Spatial statistics, Invariant Property, Variogram, Box-Cox power Transformation.

• The Mathematical Education
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• v.42 no.4
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• pp.561-577
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• 2003

Because statistical concepts are important parts in school mathematics, mathematics teachers have trained by special education model. In this study, a desirable direction of curriculum on probability and statistics at pre-service for mathematics teacher is considered. We proposed four subjects as Exploration and Analysis of Data for Mathematics Teacher, Probability and Statistics I, II for Mathematics Teacher and Statistical Software for Mathematics, and suggested the constituents and something being kept in mind for each subject.

• Journal of the Korean Society of Food Culture
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• v.19 no.3
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• pp.313-325
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• 2004

The purpose of this study was to examine Korean restaurant industry during $1979{\sim}2001$, and to review Korean restaurant industry related by statistics. Finally, to predict the Korean restaurant industry, major restaurant industry was categorized into fast food restaurants, family restaurants, pizza restaurants and ice cream restaurants. A contents analysis used to review Korea food industry yearly statistics and monthly magazine 'restaurant'. Korean food service industry yearly statistics have been published since 1980, the magazine 'Restaurant' has been published since 1985, but the statistics was recorded from 1995.

• School Mathematics
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• v.2 no.1
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• pp.1-27
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• 2000

In the past half century little effort has been made for the improvement of teaching and learning statistics compared with other parts of school mathematics. But recently data analysis has begun to play a prominant role in the national reform efforts of mathematics curricula in the United States of America and the United Kingdom. In this paper we overview modern statistical thinking differed from mathematical thinking and examine the problems of current old-style teaching of statistics. And, we discuss the current data handling(or data analysis) emphasis in the national curriculum of mathematics in the countries mentioned above. We explore the reform direction of statistics teaching; changing the philosophy of teaching statistics, teaching real data analysis, emphasis of using computer, and teaching statistical inference not as mathematics but as intuitive data-centered approach.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.563-573
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• 2012

Various methods of analysis have been proposed to understand the gene-disease relation and gene-gene interaction effect for a disease through comparison of genotype in case-control study. In this study, we proposed the method to detect a genetic association and gene-gene interaction through the use of a network graph and centrality measures that are used in social network analysis. The applicability of the proposed method was studied through an analysis of real genetic data.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.1-10
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• 2007

In this paper, we focus on churn analysis for the first successful candidates in the entrance examination on 2006 year using Clementine, data mining tool. The goal of this study is to apply decision tree including C5.0 and CART algorithms, neural network and logistic regression techniques to predict a successful candidate churn. And we analyze the churning and nochurning successful candidates and why the successful candidates churn and which successful candidates are most likely to churn in the future using data from entrance examination data of K university on 2006 year.