Analyzing Multivariate Data

James Lattin, J. Douglas Carroll, Paul E. Green

572 pages, parution le 15/04/2003

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Résumé

Offering the latest teaching and practice of applied multivariate statistics, this text is perfect for students who need an applied introduction to the subject. Lattin, Green, and Carroll have created a text that speaks to the needs of applied students who have advanced beyond the beginning level, but are not yet advanced statistics majors. Their text accomplishes this through a three-part structure. First, the authors begin each major topic by developing students' statistical intuition through geometric presentation. Then, they providing illustrative examples for support. Finally, for those courses where it will be valuable, they describe relevant mathematical underpinnings with matrix algebra.

Benefits:

Uses geometric interpretation to develop readers' intuition and provide students with a mental picture of how each method works. Mathematics is used to support the underlying intuition.
Takes a pragmatic, hands-on approach through sample problems based on real data. Each chapter offers at least one application, as well as a discussion of issues related to the proper interpretation of the results.
Accompanying student workbooks are specific to a given software package (either SAS or SPSS), and annotated program output facilitates interpretation and provides links to concepts included in the text.
Addresses important issues that come up with each application of a method. Special emphasis is placed on generalizing the results of the analysis, and suggestions are presented for testing the validity of findings.
Contains illustrations and sample problems from a wide range of areas, including psychology, sociology, and marketing research.
Follows a standard format in each chapter. This format begins by discussing a general set of research objectives, followed by some illustrative examples of problems in different areas. Then it provides an explanation of how each methods works, followed by a sample problem, application of the technique, and interpretation of results.

Contents

Overview

Introduction
Vectors and Matrixes
Regression Analysis

Analysis of Interdependence

Principal Components Analysis
Exploratory Factor Analysis
Confirmatory Factor Analysis
Multidimensional Scaling
Cluster Analysis

Analysis of Dependence

Canonical Correlation
Structural Equation Models with Latent Variables
Analysis of Variance
Discriminant Analysis
Logit Choice Models

L'auteur - James Lattin

Stanford University

L'auteur - J. Douglas Carroll

Rutgers University

L'auteur - Paul E. Green

University of Pennsylvania

Caractéristiques techniques

	PAPIER
Éditeur(s)	Thomson
Auteur(s)	James Lattin, J. Douglas Carroll, Paul E. Green
Parution	15/04/2003
Nb. de pages	572
Format	19 x 24
Couverture	Relié
Poids	1018g
Intérieur	Noir et Blanc
EAN13	9780534349745