Applied multivariate statistical analysis

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Prentice Hall, 1992 - Mathematics - 642 pages
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Explores the statistical methods for describing and analyzing multivariate data. It's goal is to provide readers with the knowledge necessary to make proper interpretations, and select appropriate techniques for analyzing multivariate dataCoverage includes: Detecting Outliers and Data Cleaning; Multivariate Quality Control; Monitoring Quality with Principal Components; and Correspondence Analysis, Biplots, and Procrustes Analysis.

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f Aspects of Multivariate Analysis
Matrix Algebra and Random Vectors
Sample Geometry and Random

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