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http://dx.doi.org/10.7465/jkdi.2015.26.2.399

Data visualization of airquality data using R software  

Oh, Youngchang (Department of Statistics, Chonnam University)
Park, Eunsik (Department of Statistics, Chonnam University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.2, 2015 , pp. 399-408 More about this Journal
Abstract
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.
Keywords
Box plot; data visualization; scatter plot matrix; three-dimensional perspective drawing; three-dimensional scatter plot;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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1 Bae, D., Park, H. and Oh, K. (2013). Big data trends and policy implications. International Telecommunications Policy Review, 25, 37-74.
2 Chambers, J. M., Cleveland, W. S., Kleiner, B. and Tukey, P. A. (1983). Graphical Methods for Data Analysis, Wadsworth.
3 Cho, J. (2014). Analysis of employee's characteristic using data visualization. Journal of the Korean Data & Information Science Society, 25, 727-736.   DOI   ScienceOn
4 Choi, K., Ham, Y. and Kim, S. (2013). Big data visualization. KSCI Review, 21, 33-43.
5 Joo, S., Jung, J. and Ryu, K. (2013). Big data technology trends, visualizations of big and public data. Smart Media Journal, 2, 37-43.
6 Kim, K. and Lee, K. (2014). A web application for open data visualization using R. Journal of the Korean Association of Geographic Information Studies, 17, 72-81.   DOI   ScienceOn
7 Lim, Y., Baek, S. and Yeon, S. (2012). Choice and focus for competitiveness of big data era. Nurimedia Korean Studies Journals, 29, 3-10.
8 Park, D. (2007). Teaching statistical graphics using R. The Korean Journal of Applied Statistics, 20, 619-634.   DOI   ScienceOn
9 Park, S. (2014). Visualization and interpretation of cancer data using linked micromap plots. Journal of the Korean Data & Information Science Society, 25, 1531-1538.   DOI   ScienceOn
10 Stephen, F. (2007). Visualizing change : an innovation in time-series analysis. Visual Business Intelligence Newsletter, September 2007.
11 Zeileis, A., Leisch, F., Hornik, K. and Kleiber, C. (2002). Strucchange: an R package for testing for structural change in linear regression models. Journal of Statistical Software, 7, 1-38.