Special Issue on Multivariate Statistical Analysis

Multivariate statistical analysis is the application of multivariate statistics, which involves observation and analysis of more than one dependent variable and one independent variable simultaneously to study the relationship between them. There are several statistical techniques for multivariate analysis, such as multiple regression analysis, cluster analysis, principal component analysis, factor analysis and etc. However, the most appropriate technique for a given study varies with the type of study and the research questions. Researches on multivariate statistical analysis are essential because a given outcome or phenomenon is usually effected by more than one factor.

The goal of this special issue is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in the area of research on the multivariate statistical analysis.

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring multivariate statistical analysis. Potential topics include, but are not limited to:

• Multiple regression analysis
• Discriminant analysis
• Cluster analysis
• Principal component analysis
• Factor analysis
• Analysis of variance
• Correspondence analysis

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue – Multivariate Statistical Analysis” should be selected during your submission.

According to the following timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

ojs@scirp.org