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While multivariate statistical methods play a prominent role in chemometrics, they are often misunderstood or unknown among research and laboratory professionals. Using only a short segment of matrix algebra for the description of methods, "Introduction to Multivariate Statistical Analysis in Chemometrics" presents simple but thorough explanations of the most important multivariate statistical methods used for analyzing chemical data. This practical guide demonstrates methods using the R software package, considering also robust methods, providing software tools, fully worked out examples, and demo data from chemistry fields. Various graphical schemes and illustrations supplement the text.