Multivariate Statistical Methods

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A01=George A. Marcoulides
A01=Scott L. Hershberger
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analysis
applied statistics
Author_George A. Marcoulides
Author_Scott L. Hershberger
canonical
Canonical Correlation
Canonical Correlation Analysis
canonical correlation methods
Canonical Variate
Canonical Variate Scores
Category=JHBC
Category=PBT
Category=UY
Cc SS
CCC CCC
Comparisonwise Error Rate
correlation
data reduction techniques
Data Set
Descriptive Discriminant Analysis
discriminant
Discriminant Function
discriminant function analysis
E3 E4 E5 E6 E7
educational psychology research
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
functions
MANOVA Procedure
matrix
multivariate analysis for social sciences
observable
Observed Correlation Matrix
Observed Variables
Predictive Discriminant Analysis
Root MSE
roy's
SAS PROCs
SAS programming examples
sscp
SSCP Matrix
V2 V3 V4 V5 V6
V4 V5 V6 V7 V8
variable

Product details

  • ISBN 9780805825725
  • Weight: 620g
  • Dimensions: 152 x 229mm
  • Publication Date: 01 Feb 1997
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis.

An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is pointing out the analogy between a common univariate statistical technique and the corresponding multivariate method. Many computer examples--drawing on SAS software --are used as demonstrations.

Throughout the book, the computer is used as an adjunct to the presentation of a multivariate statistical method in an empirically oriented approach. Basically, the model adopted in this book is to first present the theory of a multivariate statistical method along with the basic mathematical computations necessary for the analysis of data. Subsequently, a real world problem is discussed and an example data set is provided for analysis. Throughout the presentation and discussion of a method, many references are made to the computer, output are explained, and exercises and examples with real data are included.

Marcoulides, George A.; Hershberger, Scott L.

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