Kniha Applied Multivariate Analysis Neil H. Timm

Applied Multivariate Analysis

Autor: Neil H. Timm
Jazyk: Angličtina
Väzba: Pevná
Dostupnosť: Skladom u dodávateľa
Odosielame za 10-13 dní
127.12
This book provides a broad overview of the basic theory and methods of applied multivariate analysis...

Informácie o knihe

Autor
Jazyk
Angličtina
Väzba
Kniha - Pevná
Vydalo
2002
Stránok
695
EAN
9780387953472
ISBN
0387953477
Enbook ID
01384362
Hmotnosť
1514
Rozmery
187 x 265 x 47

Kompletný popis

This book provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0.This textbook provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0. The book includes an overview of vectors, matrices, multivariate distribution theory, and multivariate linear models. Topics discussed include multivariate regression, multivariate analysis of variance for fixed and mixed models, seemingly unrelated regression models and repeated measurement models. While standard procedures for estimating model parameters and testing multivariate hypotheses, as well as simultaneous test procedures, are discussed and illustrated in the text, the text also includes tests of multivariate normality with chi-square and beta plots, tests of multivariate nonadditivity, tests of covariance structure, tests of nonnested hypotheses, and the assessment of model assumptions. Other topics illustrated in the text include discriminant and classification analysis, principal component analysis, canonical correlation analysis, exploratory factor analysis, cluster analysis, multidimension scaling, and structural equation modeling. The text should appeal to practitioners, researchers, and applied statisticians. It may be used in a one-semester course in applied multivariate analysis for practitioners and researchers, or as a two-semester course for majors in applied statistics. Because most data analyzed in the social and behavioral sciences and other disciplines involve many continuous variables, the techniques and examples. SAS programs for this book are available on the Springer website.

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