• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.399-408
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• 2015

This paper presented airquality data through data visualization in several ways and described its characteristics related to statistical methods for analysis. Software R was used for visualization tools. The airquality data was measured in New York city from May to September of year 1973. First, simple, exploratory data analysis was done in terms of both data visualization and analysis to find out univariate characteristics. Then through data transformation and multiple regression analysis, model for describing the airquality level was found. Also, after some data categorization, overall feature of the data was explored using box plot and three-dimensional perspective drawing and scatter plot.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.999-1007
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• 2013

This research shows several types of moving pictures from the data: 1) the word cloud of Korean texts, 2) the heat map of n ${\times}$ p matrices, 3) the moving image of p ${\times}$ p scatterplot matrix, 4) the local projective display of k clusters (Huh and Lee, 2012). Moving pictures may reveal the hidden information and beauty of the datasets and ignite the curiosity of information consumers. Video files are attached.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.893-904
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• 2011

The lecture of the experimental designs consists of two main part-experimental designs and model analysis. Mostly, the progress of the visualization has been made on a model analysis. As the visualization of experimental designs, we can consider the visualization of Latin squares, supersaturated designs, and balanced incomplete block designs. We can propose the design plots as well as use the scatterplots and the scatterplot matrices for the visualization of experimental designs. Through the visualization of experimental designs, we can use the synergy effect in teaching the lecture of the experimental designs.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.177-190
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• 2001

전통적으로 많이 사용하는 군집분석의 방법들은 개체간의 거리를 고려하여 이들을 분류해 내는 것이며, 따라서 거리 측정 방법에 따라 여러 형태의 군집분석 방법이 나타나게 된다. 어떤 방법을 적용하던 간에 그 결과는 고정된 수치로써 나타난다. 다차원 자료의 구조파악이 몇 개의 수치로 나타나게 되면 어쩔 수 없이 정보의 손실이 발생하게 된다. 이를 보완하기 위해 시각적 매체를 동원하여 다차원 자료의 구조를 파악하는 연구가 있었으며, 이를 시각적 군집분석이라고 명명하고 있다. 본 연구에서는 시각적 군집분석에 대한 기본적 개념과 이를 위한 통계 도형의 활용, 구현방법 등에 대해 살펴보기로 한다.