There are a lot of software in the market which can help you analyse the existing data like ,The Unscrambler from CAMO Software is a pretty good one ...All these softwares would have rows and columns to insert the data and then carry out PCA or PLS or what ever you are looking out for ..
Multivariate analysis techniques enable researchers to analyze the relationships between multiple variables at once, providing more nuanced insights than univariate or bivariate methods. Some common multivariate techniques used in marketing research include: Multiple regression analysis Factor analysis Cluster analysis Discriminant analysis Conjoint analysis
Harald Martens has written, Multivariate data analysis of quality.
James H. Bray has written: 'Multivariate analysis of variance' -- subject(s): Multivariate analysis, Analysis of variance
Richard H. Lindeman has written: 'Introduction to bivariate and multivariate analysis' -- subject(s): Multivariate analysis
Clifford E. Lunneborg has written: 'Elementary multivariate analysis for the behavioral sciences' -- subject(s): Multivariate analysis
When you carrying out multivariate analyses.
Yvonne M. M. Bishop has written: 'Discrete multivariate analysis: theory and practice' -- subject(s): Multivariate analysis
The main objective of multivariate statistics analysis is to provide information to companies who need that specific information. This method gives a good overview of information.
George H. Dunteman has written: 'Introduction to linear models' -- subject(s): Regression analysis, Linear models (Statistics) 'Introduction to multivariate analysis' -- subject(s): Multivariate analysis
Richard J. Harris has written: 'A primer of multivariate statistics' -- subject(s): Multivariate analysis
Chester Lewellyn Olson has written: 'A Monte Carlo investigation of the robustness of multivariate analysis of variance' -- subject(s): Monte Carlo method, Multivariate analysis
a set of techniques used for analysis of data sets that contain more than one variable, and the techniques are especially valuable when working with correlated variables.