Multivariate Statistical Methods

ISBN-10: 1584884142

ISBN-13: 9781584884149

Edition: 3rd 2004 (Revised)

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Description: This is a thoroughly revised, updated edition of a best-selling introductory textbook and primer. Topics new to this edition include confirmatory factor analysis, handling missing values, and the emerging techniques of data mining and neural networks. It also contains an appendix comparing and contrasting statistical software packages.

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Book details

List price: $71.95
Edition: 3rd
Copyright year: 2004
Publisher: CRC Press LLC
Publication date: 7/6/2004
Binding: Paperback
Pages: 224
Size: 6.25" wide x 9.25" long x 0.50" tall
Weight: 0.704
Language: English

The material of multivariate analysis
Examples of multivariate data
Preview of multivariate methods
The multivariate normal distribution
Computer programs
Graphical methods
Chapter summary
References
Matrix algebra
The need for matrix algebra
Matrices and vectors
Operations on matrices
Matrix inversion
Quadratic forms
Eigenvalues and eigenvectors
Vectors of means and covariance matrices
Further reading
Chapter summary
References
Displaying multivariate data
The problem of displaying many variables in two dimensions
Plotting index variables
The draftsman's plot
The representation of individual data points
Profiles of variables
Discussion and further reading
Chapter summary
References
Tests of significance with multivariate data
Simultaneous tests on several variables
Comparison of mean values for two samples: the single variable case
Comparison of mean values for two samples: the multivariate case
Multivariate versus univariate tests
Comparison of variation for two samples: the single-variable case
Comparison of variation for two samples: the multivariate case
Comparison of means for several samples
Comparison of variation for several samples
Computer programs
Chapter summary
Exercise
References
Measuring and testing multivariate distances
Multivariate distances
Distances between individual observations
Distances between populations and samples
Distances based on proportions
Presence-absence data
The Mantel randomization test
Computer programs
Discussion and further reading
Chapter summary
Exercise
References
Principal components analysis
Definition of principal components
Procedure for a principal components analysis
Computer programs
Further reading
Chapter summary
Exercises
References
Factor analysis
The factor analysis model
Procedure for a factor analysis
Principal components factor analysis
Using a factor analysis program to do principal components analysis
Options in analyses
The value of factor analysis
Computer programs
Discussion and further reading
Chapter summary
Exercise
References
Discriminant function analysis
The problem of separating groups
Discrimination using Mahalanobis distances
Canonical discriminant functions
Tests of significance
Assumptions
Allowing for prior probabilities of group membership
Stepwise discriminant function analysis
Jackknife classification of individuals
Assigning of ungrouped individuals to groups
Logistic regression
Computer programs
Discussion and further reading
Chapter summary
Exercises
References
Cluster analysis
Uses of cluster analysis
Types of cluster analysis
Hierarchic methods
Problems of cluster analysis
Measures of distance
Principal components analysis with cluster analysis
Computer programs
Discussion and further reading
Chapter summary
Exercises
References
Canonical correlation analysis
Generalizing a multiple regression analysis
Procedure for a canonical correlation analysis
Tests of significance
Interpreting canonical variates
Computer programs
Further reading
Chapter summary
Exercise
References
Multidimensional scaling
Constructing a map from a distance matrix
Procedure for multidimensional scaling
Computer programs
Further reading
Chapter summary
Exercise
References
Ordination
The ordination problem
Principal components analysis
Principal coordinates analysis
Multidimensional scaling
Correspondence analysis
Comparison of ordination methods
Computer programs
Further reading
Chapter summary
Exercise
References
Epilogue
The next step
Some general reminders
Missing values
References
Computer packages for multivariate analyses
References
Author Index
Subject Index
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