Applied Multivariate Statistical Analysis
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 d...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2003, 2003
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| Edition: | 1st ed. 2003 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- I Descriptive Techniques
- 1 Comparison of Batches
- II Multivariate Random Variables
- 2 A Short Excursion into Matrix Algebra
- 3 Moving to Higher Dimensions
- 4 Multivariate Distributions
- 5 Theory of the Multinormal
- 6 Theory of Estimation
- 7 Hypothesis Testing
- III Multivariate Techniques
- 8 Decomposition of Data Matrices by Factors
- 9 Principal Components Analysis
- 10 Factor Analysis
- 11 Cluster Analysis
- 12 Discriminant Analysis
- 13 Correspondence Analysis
- 14 Canonical Correlation Analysis
- 15 Multidimensional Scaling
- 16 Conjoint Measurement Analysis
- 17 Applications in Finance
- 18 Highly Interactive, Computationally Intensive Techniques
- A Symbols and Notation
- B Data
- B.1 Boston Housing Data
- B.2 Swiss Bank Notes
- B.3 Car Data
- B.4 Classic Blue Pullovers Data
- B.5 U.S. Companies Data
- B.6 French Food Data
- B.7 Car Marks
- B.8 French Baccalauréat Frequencies
- B.9 Journaux Data
- B.10 U.S. Crime Data
- B.11 Plasma Data
- B.12 WAIS Data
- B.13 ANOVA Data
- B.14 Timebudget Data
- B.15 Geopol Data
- B.16 U.S. Health Data
- B.17 Vocabulary Data
- B.18 Athletic Records Data
- B.19 Unemployment Data
- B.20 Annual Population Data