A first course in multivariate statistics

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a first course in multivariate statistics

A First Course in Multivariate Statistics by Bernhard Flury

Multivariate statistical methods have evolved from the pioneering work of Fisher, Pearson, Hotelling, and others, motivated by practical problems in biological and other sciences. In the past fifty years, the field has grown rapidly, largely due to the availability of computers that make the calculations feasible. This book gives a comprehensive and self-contained introduction, carefully balancing mathematical theory and practical applications. Unique features of A First Course in Multivariate Statistics include the presentation of the EM algorithm for maximum likelihood estimation with incomplete data, resampling-based methods of testing, a brief introduction to the theory of elliptical distributions, and a comparison of linear and quadratic classification rules. Examples from biology, anthropology, chemistry, and other areas are worked out in detail. The book contains a wealth of exercises, ranging from easy to advanced, making it an ideal text for the classroom. Many graphical illustrations help the student develop an intuitive understanding of the mathematical concepts.
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Published 16.12.2018

Multivariate Statistical Analysis Part I: Introduction and Mean Comparison (with R demonstration)

ISBN 13: 9780387982069

It seems that you're in Germany. We have a dedicated site for Germany. The style of this book reflects my beliefthat the common distinction between multivariate statistical theory and multivariate methods is artificial and should be abandoned. I hope that readers who are mostly interested in practical applications will find the theory accessible and interesting. Similarly I hope to show to more mathematically interested students that multivariate statistical modelling is much more than applying formulas to data sets.

Bibliographic Information

Introduction to Multivariate Statistics - Course Syllabus Review

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