Metode și tehnici de analiză multidimensională a datelor. Suport de curs
Methods and techniques of multidimensional data analysis. Lecture notes

Author(s): Andreea MURARU
Subject(s): Economy
Published by: EDITURA ASE
Keywords: data analysis; principal components analysis (PCA); factor analysis; correspondence analysis; cluster analysis; discriminant analysis
Summary/Abstract: The book presents the most commonly used tools, methods and techniques of multivariate analysis and it is mostly designed for bachelor and graduate students. It has 8 chapters, grouped into 3 parts, as follows: (i) the first part (containing 3 chapters) is a review of fundamentals of matrix algebra, probability theory and statistics with a greater focus on the concepts underlying the mathematical models of the various data analysis techniques described further in the book; (ii) the second part is dedicated to dimensionality reduction methods, covering 3 types of analysis each of them described in a separate chapter: principal component analysis, factor analysis and correspondence analysis; and (iii) the third part deals (within two chapters) with pattern recognition techniques: cluster analysis and discriminant analysis.Besides the technical and mathematical descriptions, the chapters focusing on methods of multivariate data analysis also include a case study on real data, and some examples to clarify the more complex parts.

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