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Applied Multivariate Statistical Analysis

✍ Scribed by Wolfgang Härdle, Léopold Simar (auth.)


Publisher
Springer Berlin Heidelberg
Year
2003
Tongue
English
Leaves
479
Category
Library

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✦ Synopsis


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.

✦ Table of Contents


Front Matter....Pages i-9
Front Matter....Pages 11-11
Comparison of Batches....Pages 13-54
Front Matter....Pages 55-55
A Short Excursion into Matrix Algebra....Pages 57-80
Moving to Higher Dimensions....Pages 81-118
Multivariate Distributions....Pages 119-154
Theory of the Multinormal....Pages 155-171
Theory of Estimation....Pages 173-182
Hypothesis Testing....Pages 183-216
Front Matter....Pages 217-217
Decomposition of Data Matrices by Factors....Pages 219-232
Principal Components Analysis....Pages 233-273
Factor Analysis....Pages 275-299
Cluster Analysis....Pages 301-321
Discriminant Analysis....Pages 323-340
Correspondence Analysis....Pages 341-359
Canonical Correlation Analysis....Pages 361-372
Multidimensional Scaling....Pages 373-392
Conjoint Measurement Analysis....Pages 393-406
Applications in Finance....Pages 407-419
Highly Interactive, Computationally Intensive Techniques....Pages 421-441
Back Matter....Pages 443-487

✦ Subjects


Statistical Theory and Methods; Statistics for Business/Economics/Mathematical Finance/Insurance; Economic Theory


📜 SIMILAR VOLUMES


Applied Multivariate Statistical Analysi
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This is probably the best applied statistics book I have ever read. It is not one of the "for dummies" book, it does use some linear algebra and requires some knowledge of elementary statistics, but at the same time it is very clear and understandable. I think this is the only reasonable approach -

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With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in a way that

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I. Descriptive Techniques: Comparison of Batches.- II. Multivariate Random Variables: A Short Excursion into Matrix Algebra.- Moving to Higher Dimensions.- Multivariate Distributions.- Theory of the Multinormal.- Theory of Estimation.- Hypothesis Testing.- III. Multivariate Techniques: Regression

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This textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields, and all the examples involve high to u