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Applied multivariate statistics with R / Daniel Zelterman.

Second edition.

9783031130052 (electronic bk.)
3031130057 (electronic bk.)
9783031130045
3031130049

Cham : Springer, 2022.

English

1 online resource : illustrations (black and white, and colour).

10.1007/978-3-031-13005-2 doi

QA278

519.53502855133

Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.

Previous edition: 2015.

Includes bibliographical references and index.

Access limited to authorized users.

Description based on print version record.

Statistics for biology and health.

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