Multivariate Statistics for Understanding Complex Data

Target group

Course structure

Overview of Multivariate Methods

• examples of multivariate analyses
• matrix algebra concepts

Principal Components Analysis Using the PRINCOMP procedure

• principal component analysis for dimension reduction

Exploratory Factor Analysis Using the FACTOR Procedure

• factor analysis for latent variable measurement
• factor rotation

Multidimensional Preference Analysis Using the PRINQUAL and TRANSREG procedures

• plotting high-dimensional preference data
• mapping preferences to other characteristics

Correspondence Analysis Using the CORRESP Procedure

• understanding complex associations among categorical variables

Canonical Variate Analysis Using the CANCORR and CANDISC Procedures

• multivariate dimensions reduction for two sets of variables

Discriminant Function Analysis Using the DISCRIM Procedure

• classification into groups
• linear discriminant analysis
• quadratic discriminant analysis
• empirical validation

Partial Least Squares Regression Using the PLS Procedure

• PLS for one target variable
• PLS for many targets
• PLS for predictive modeling