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主成分分析(PCA)和聚类分析(CA)方法在SWB数据分析中的应用 被引量:2

The Application of PCA and CA Methods in the Study of SWB
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摘要 在主观幸福感(SWB)的研究中,相关分析,回归或多元回归分析经常被用于数据的统计分析.考虑到SWB数据中通常包含着许多的变量,过于简单的分析处理方法将导致数据中信息的流失.本文将主成分分析(PCA)和聚类分析(CA)方法应用到SWB数据分析上,力求对SWB的原始数据有更加详细的了解和认识,并为今后类似问题的数据分析提供一个新的途经. In the research of SWB (Subjective Well - Being) , researchers usually apply the regression and multi - variant regression for the data analysis. However, the data about SWB research often includes many variants and contains lots of potential information. It is hard to dig out more detailed information by the simple methods like the regression. In the article, the PCA (Principal Component Analysis) and CA (Cluster Analysis) have been used to do data analysis on the SWB, and magnificent results have been obt...
作者 罗先文
出处 《玉溪师范学院学报》 2004年第12期25-30,共6页 Journal of Yuxi Normal University
关键词 主观幸福感(SWB) 主成分分析(PCA) 聚类分析(CA) 文化体系 SWB (Subjective Well -Being) PCA (Principal Component Analysis) CA (Cluster Analysis) Culture System
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