Applied Multivariate Statistical Analysis

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Springer Science & Business Media, Mar 9, 2013 - Mathematics - 486 pages
Most of the observable phenomena in the empirical sciences are of multivariate nature. This book presents the tools and concepts of multivariate data analysis with a strong focus on applications. The text is devided into three parts. The first part is devoted to graphical techniques describing the distributions of the involved variables. The second part deals with multivariate random variables and presents from a theoretical point of view distributions, estimators and tests for various practical situations. The last part covers multivariate techniques and introduces the reader into the wide basket of tools for multivariate data analysis. The text presents a wide range of examples and 228 exercises.
 

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Contents

Descriptive Techniques
7
Canonical Correlation Analysis
8
A Short Excursion into Matrix Algebra 57
56
Moving to Higher Dimensions
81
Multivariate Distributions
119
Theory of the Multinormal
155
Theory of Estimation
173
Hypothesis Testing
183
Swiss Bank Notes
448
Car Data
452
Classic Blue Pullovers Data
454
U S Companies Data
455
French Food Data
457
Car Marks
458
French Baccalauréat Frequencies
459
Journaux Data
460

Decomposition of Data Matrices by Factors 219
218
Principal Components Analysis
233
Factor Analysis
275
Cluster Analysis 301
300
Discriminant Analysis
323
Correspondence Analysis
341
Multidimensional Scaling
373
Conjoint Measurement Analysis
393
Applications in Finance
407
Highly Interactive Computationally Intensive Techniques
421
Boston Housing
439
Exercises
440
A Symbols and Notation 443
442
B Data
447
U S Crime Data
461
Plasma Data
463
WAIS Data
464
ANOVA Data
466
Timebudget Data
467
Geopol Data
469
U S Health Data
471
Vocabulary Data
473
Athletic Records Data
475
Unemployment Data
477
Annual Population Data
478
Bibliography
479
Index
483
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