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http://dx.doi.org/10.17661/jkiiect.2018.11.2.169

Multi-dimension Categorical Data with Bayesian Network  

Kim, Yong-Chul (Department of Logistic and Statistical Information, Yongin University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.11, no.2, 2018 , pp. 169-174 More about this Journal
Abstract
In general, the methods of the analysis of variance(ANOVA) for the continuous data and the chi-square test for the discrete data are used for statistical analysis of the effect and the association. In multidimensional data, analysis of hierarchical structure is required and statistical linear model is adopted. The structure of the linear model requires the normality of the data. A multidimensional categorical data analysis methods are used for causal relations, interactions, and correlation analysis. In this paper, Bayesian network model using probability distribution is proposed to reduce analysis procedure and analyze interactions and causal relationships in categorical data analysis.
Keywords
Bayesian network; categorical data; conditional probability; odds ratio; survey analysis;
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