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Statistics - Business, Economics & Finance | Applied Multivariate Statistical Analysis

Applied Multivariate Statistical Analysis

Härdle, Wolfgang Karl, Simar, Léopold

3rd ed. 2012, XVII, 516 p. 424 illus., 28 illus. in color.

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  • Revised and updated third edition offers a broader range of material
  • Wide scope of methods and applications, making this a comprehensive treatment of the subject
  • A wealth of examples and exercises—ideal for students in economics and finance
  • Quantlets in R and Matlab available online

Most of the observable phenomena in the empirical sciences are of a multivariate nature.  In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices.  In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication.  In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior.  The underlying data structure of these and many other quantitative studies of applied sciences is multivariate.  Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data.  The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics.  All chapters have exercises that highlight applications in different fields.

The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features

  • A new Chapter on Regression Models has been added
  • All numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.

Content Level » Graduate

Keywords » Cluster Analysis - Conjoint Measurement Analysis - Discriminant Analysis - Hypothesis Testing - Multyvariate Analysis - Projection Persuit - Sliced Inverse Regression

Related subjects » Business, Economics & Finance - Economic Theory - Quantitative Finance - Statistical Theory and Methods

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