# Matrix-Based Introduction to Multivariate Data Analysis

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• Enables even readers without knowledge of matrices to grasp their operations to learn multivariate data analysis in matrix forms
• Emphasizes what model underlies an analysis procedure and what function is optimized for estimating model parameters as the fastest way to understand the procedure
• Introduces plain numerical illustrations of the purposes for which procedures are utilized, followed by mathematical descriptions for an intuitive understanding of those purposes
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eBook 67,40 €
price for Spain (gross)
• ISBN 978-981-10-2341-5
• Digitally watermarked, DRM-free
• Included format: PDF, EPUB
• ebooks can be used on all reading devices
Softcover 83,19 €
price for Spain (gross)

This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter. This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on singular value decomposition among theorems in matrix algebra. The book begins with an explanation of fundamental matrix operations and the matrix expressions of elementary statistics, followed by the introduction of popular multivariate procedures with advancing levels of matrix algebra chapter by chapter. This organization of the book allows readers without knowledge of matrices to deepen their understanding of multivariate data analysis.

• Elementary Matrix Operations

Pages 3-16

• Intravariable Statistics

Pages 17-28

• Inter-variable Statistics

Pages 29-43

• Regression Analysis

Pages 47-62

• Principal Component Analysis (Part 1)

Pages 63-77

eBook 67,40 €
price for Spain (gross)
• ISBN 978-981-10-2341-5
• Digitally watermarked, DRM-free
• Included format: PDF, EPUB
• ebooks can be used on all reading devices
Softcover 83,19 €
price for Spain (gross)

## Bibliographic Information

Bibliographic Information
Book Title
Matrix-Based Introduction to Multivariate Data Analysis
Authors
2016
Publisher
Springer Singapore
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-10-2341-5
DOI
10.1007/978-981-10-2341-5
Softcover ISBN
978-981-10-9595-5
Edition Number
1
Number of Pages
XIII, 301
Number of Illustrations
47 b/w illustrations, 8 illustrations in colour
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