understandable for non-mathematicians, this third edition includes new features such as a chapter on regression models. All the numerical examples are reproduced in MATLAB...
observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development...
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Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
events are included. Cram101 Textbook Outlines gives all of the outlines, highlights, notes for your textbook with optional online practice tests. Only Cram101 Outlines are Textbook Specific. Cram101 is NOT the Textbook. Accompanys: 9780131877153
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 featuresA new Chapter on Regression Models has been addedAll numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.
17,7 x 23,6 cm, Kartoniert (TB), EnglischFor courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
* Alle Preise inkl. gesetzlicher MwSt und ggf. zzgl. Versandkosten. Preise, Verfügbarkeit und Versandkosten können im jeweiligen Shop zwischenzeitlich geändert worden sein, da eine Echtzeit-Aktualisierung technisch nicht möglich ist. Maßgeblich sind immer die Preise und Angaben auf der Händlerseite. Alle Angaben ohne Gewähr.
Applied Multivariate Statistical Analysis / Wolfgang Karl Härdle, Leopold Simar
Haupteigenschaften
Produktform: Einband - flexibel (Paperback)
Nummer der Ausgabe: 2
Ausgabe: 2., nd ed.
Erscheinungsdatum: 2007
Seitenzahl / arabisch: 458
Zielgruppe: Graduate
Seitenzahl / römisch: XII
ISBN: 3540722432
EAN: 9783540722434
Bestellnummer : 12057573
Titel: Applied Multivariate Statistical Analysis
Sprache: Englisch
Kategorie: Mathematik / Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik
Medium: Hardcover, Softcover
Kurzbeschreibung: 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 as it presents tools and concepts in a way that is understandable for non-mathematicians.