• The Korean Journal of Applied Statistics
• /
• v.26 no.6
• /
• pp.959-975
• /
• 2013

The SAS macro faces program by Friendly (1992) is for Chernoff face analysis, which is one of methods for the visualization representation of multivariate data. In this paper, we examined 18 face features used in the program and presented the modified program depending on the definition of a good face in days present. In addition, a good bank evaluation for 15 domestic banks was performed through Chernoff face analysis based on 11 bank economic indicators representing stability, the consumer satisfaction, soundness, and banks profitability.

• Journal of the Korean Society for Library and Information Science
• /
• v.51 no.1
• /
• pp.271-287
• /
• 2017

This study aims to conduct a big data analysis of public library operations and uses of 16 metropolitan local government of Korea by using the Chernoff face method. This study is the first to use the Chernoff face method for big data analysis of library services in library and information research. The association of variables and human facial features was decided by survey. The study reveals that in general the provincial governments in Korea operate more libraries, invest more budgets, allocate more staff and hold more collections than metropolitan cities. This administration resulted in more use of libraries in provincial governments than metropolitan cities.