Multivariate Data Analysis

Abstract

This chapter contains sections titled: General Remarks Graphical Methods of Data Presentation Introduction Transformation Visualization of Similar Features – Correlations Similar Objects or Groups of Objects Nesting Techniques Star Plots Pictoral Representation Functional Representation Representation of Groups Box-Whisker Plots Multiple Box-Whisker Plots Limitations Cluster Analysis Objectives of Cluster Analysis Similarity Measures and Data Preprocessing Clustering Algorithms CA Calculations Demonstrated with a Simple Example Typical CA Results Illustrated with an Extended Example Principal Components Analysis and Factor Analysis Description of Principal Components Analysis PCA Calculations Demonstrated with a Simple Example Description of Factor Analysis Typical FA Results Illustrated with an Extended Example Canonical Correlation Analysis Description of Canonical Correlation Analysis Typical CCA Results Illustrated with an Extended Example Multivariate Analysis of Variance and Discriminant Analysis General Description DA Calculations Demonstrated with a Simple Example Typical DA Results Illustrated with an Extended Example Multivariate Modeling of Causal Dependencies Multiple Regression Partial Least Squares Method Simultaneous Equations and Path Analysis

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