PORTO-
FREI

An Introduction to Applied Multivariate Analysis with R

von Everitt, Brian / Hothorn, Torsten   (Autor)

The majority of data sets collected by researchers in all disciplines are multivariate. This book comprehensively covers a variety of multivariate analysis techniques using R. It provides extensive examples of R code used to apply the multivariate techniques.

Buch (Kartoniert)

EUR 78,00

Alle Preisangaben inkl. MwSt.

Auch verfügbar als:

  Lieferzeit ca. 2 bis 4 Wochen
(Besorgungstitel, verlagsbedingte Lieferzeit ca. 2 bis 4 Wochen)

Versandkostenfrei*

Dieser Artikel kann nicht bestellt werden.
 

Produktbeschreibung

The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.

An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data. 

Inhaltsverzeichnis

Multivariate data and multivariate analysis.- Looking at multivariate data: visualization.- Principal components analysis.- Multidimensional scaling.- Exploratory factor analysis.- Cluster analysis.- Confirmatory factor analysis and structural equation models.- The analysis of repeated measures data.- 

Autoreninfo


Brian Everitt is Professor Emeritus at King's College, London. He is the author of over 50 books on statistics.

Torsten Hothorn is Professor of Biostatistics in the Faculty of Mathematics, Computer Science and Statistics at Ludwig-Maximilians-Universität München in Germany. 

Mehr vom Verlag:

k.A.

Mehr aus der Reihe:

Use R!

Mehr vom Autor:

Everitt, Brian / Hothorn, Torsten

Produktdetails

Medium: Buch
Format: Kartoniert
Seiten: 274
Sprache: Englisch
Erschienen: Mai 2011
Auflage: 2011 edition
Sonstiges: 978-1-4419-9649-7
Maße: 233 x 158 mm
Gewicht: 451 g
ISBN-10: 1441996494
ISBN-13: 9781441996497
Verlagsbestell-Nr.: 12242818

Bestell-Nr.: 10306340 
Libri-Verkaufsrang (LVR):
Libri-Relevanz: 0 (max 9.999)
Bestell-Nr. Verlag: 12242818

Ist ein Paket? 0
Rohertrag: 3,65 €
Porto: 1,84 €
Deckungsbeitrag: 1,81 €

LIBRI: 1881140
LIBRI-EK*: 69.25 € (5%)
LIBRI-VK: 78,00 €
Libri-STOCK: 0
LIBRI: 018 Besorgungstitel * EK = ohne MwSt.
P_SALEALLOWED: WORLD
DRM: 0
0 = Kein Kopierschutz
1 = PDF Wasserzeichen
2 = DRM Adobe
3 = DRM WMA (Windows Media Audio)
4 = MP3 Wasserzeichen
6 = EPUB Wasserzeichen

UVP: 2 
Warengruppe: 26280 

KNO: 29428396
KNO-EK*: 44.69 € (25%)
KNO-VK: 74,89 €
KNO-STOCK: 0
KNO-MS: 97

KNO-SAMMLUNG: Use R!
P_ABB: 92 schwarz-weiße Abbildungen, 21 schwarz-weiße Tabellen
KNOABBVERMERK: 2011. xiv, 274 S. XIV, 274 p. 92 illus. 235 mm
KNOSONSTTEXT: 978-1-4419-9649-7
Einband: Kartoniert
Auflage: 2011 edition
Sprache: Englisch
Beilage(n): Book

Alle Preise inkl. MwSt. , innerhalb Deutschlands liefern wir immer versandkostenfrei . Informationen zum Versand ins Ausland .

Kostenloser Versand *

innerhalb eines Werktages

OHNE RISIKO

30 Tage Rückgaberecht

Käuferschutz

mit Geld-Zurück-Garantie