Multivariate Analysis Methods: Application of Statistical Software

Author: Chen Zhengchang, Cheng Binglin, et al
Publisher:
Publish Date: 2005-04-01
Features: In the research of social and behavioral sciences, with the increasing complexity of research methods and the widespread use of personal computers, the opportunity to apply multivariate statistical methods to analyze data has also increased accordingly. Especially in recent years, the number of graduate students in universities has been increasing year by year. Based on the need for writing theses, familiarity with multivariate statistical methods and the use of statistical software packages has become an indispensable skill. This book introduces eleven commonly used methods, including multiple regression analysis, canonical correlation analysis, discriminant analysis, hypothesis testing of means, multivariate analysis of variance (MANOVA), principal component analysis, factor analysis, cluster analysis, multidimensional scaling, structural equation modeling, and hierarchical linear modeling. In addition to theoretical explanations, various statistical software are applied with real data for interpretation, and statistical summaries are provided, combining both theoretical and practical aspects. This enables readers who are new to multivariate analysis to navigate various statistical software with ease.