• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.619-634
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• 2007

It is well known that graphical display is critical to data analysis. A lot of research for data visualization has been done, so many effective graphical tools are now available. With the proper use of these graphical tools, we can penetrate the complex structure of data set easily. To enjoy the benefit of the powerful graphical display, the choice of the statistical software is very crucial. R is a popular open source software tool for statistical analysis and graphics, and can provide the very powerful graphics facilities. Moreover, many researchers believe that R is the best software for statistical graphics. In this paper, we would like to discuss what we teach and how we teach in statistical graphics course using R.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.175-195
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• 2000

In this study, we developed a statistical software for measurement systems analysis. This software is patterned after the Measurement Systems Analysis Reference Manual developed by the Automotive Industry Action Group (AIAG). This software includes stability analysis, bias and linearity analysis, and gage R&R studies. This software was developed by using Delphi(version 4.0) and can be implemented on MS Windows 95 or higher level.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.31-55
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• 2007

R is an open source language for statistical computing and graphics based on the ACM software award-winning S language. R is widely used for data analysis and has become a major vehicle for making available new statistical methodology. This paper presents an overview of the design philosophy and the development model for R, reviews the basic capabilities of the system, and outlines some current projects that will influence future developments of R.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.257-266
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• 2012

R is a free software for statistical analysis that provides simple interfaces to other application programs. Many people are trying to learn R, but it is difficult to learn R compared to commercial software such as SPSS or SAS, and it is cumbersome to provide an environment to teach R. Thus, it is essential to provide a new web-based R environment for novice users or for laboratory use. We developedWebER (a web-based R environment) using PHP on the Linux apache server. WebER can be easily used by any R user because we implemented the same functions as the basic Rgui such as editing R program, generating the text, image outputs, errors and warnings. It is also possible for multi-users to access WebER.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.87-105
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• 2020

Statistical engineering contains the design of experiments, quality control/management, and reliability engineering. R is a free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. R package has many functions and libraries for statistical engineering. We can use R package as a useful tool for statistical engineering. This paper shows the applications of R package for statistical engineering and suggests a R Task View for statistical engineering.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.172-178
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• 1996

In this study, we developed a software for statistical process control. This software presents $\bar{x}$, R, CUSUM, EWMA control chart and process capability index. In this system, statistical process control methods are integrated into the automated method on a real time base. It is available in process control of specified type and can be performed on personal computer with network system.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.117-124
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• 2015

As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.485-502
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• 2019

Theoretical statistics is a calculus based course. However, there are limitations to learn theoretical statistics when students do not know enough calculus techniques. Mathematical softwares (computer algebra systems) that enable calculus manipulations help students understand statistical concepts, by avoiding the difficulties of calculus. In this paper, we introduce mathematical software such as Maxima and Wolfram Alpha. To foster statistical concepts in theoretical statistics education, we present three examples that consist of mathematical derivations using wxMaxima and statistical simulations using R.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.95-111
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• 2010

Recently, there have been lots of study for disease-genetic association using SNPs and haplotypes. Statistical methods and tools for various types of data are developed by many researchers. However, there is no unified software which can handle most of major analysis, and the methods and manners to deal with data are quite different through softwares. And thus it is not easy to researcher to choose proper software. In this study, we devide analyzing procedures into three steps: preliminary analysis, population-based analysis and family-based analysis. We review the statistical methods for each step and compare the features of the FBAT, SAS/Genetics, SAGE and R as major integrating softwares for genetic study.