Applied Multivariate Statistical Analysis

Hardle, Wolfgang und Leopold Simar:

ISBN 10: 3540722432 / ISBN 13: 9783540722434

Published by Springer Berlin Heidelberg, 2008

About this Item

472 S. Innerhalb Deutschlands Versand je nach Größe/Gewicht als Großbrief bzw. Bücher- und Warensendung mit der Post oder per DHL. Rechnung mit MwSt.-Ausweis liegt jeder Lieferung bei. Sprache: Englisch Gewicht in Gramm: 708 Taschenbuch, Maße: 15.49 cm x 2.72 cm x 23.5 cm.

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Bibliographic Details

• Title: Applied Multivariate Statistical Analysis
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2008
• Language: English
• ISBN 10: 3540722432
• ISBN 13: 9783540722434
• Binding: Soft cover
• Edition: 2nd ed. 2007.
• Condition: Gut
• Weight: 708 grams
• Seller catalogs:
  • Varia

About this title

Synopsis

With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility. This is because, in its focus on applications, the 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. In this second edition a wider scope of methods and applications of multivariate statistical analysis is introduced. All quantlets have been translated into the R and Matlab language and are made available online.

From the Back Cover

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.