Applied Multivariate Statistics with R

Zelterman, Daniel

ISBN 10: 3031130049 / ISBN 13: 9783031130045

Published by Springer International Publishing, 2023

About this Item

Zustand: Sehr gut | Seiten: 484 | Sprache: Englisch | Produktart: Bücher | 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 theclustering 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.

Seller Inventory # 41383096/2

Bibliographic Details

• Title: Applied Multivariate Statistics with R
• Publisher: Springer International Publishing
• Publication Date: 2023
• Language: English
• ISBN 10: 3031130049
• ISBN 13: 9783031130045
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: Sehr gut
• Seller catalogs:
  • Bücher

About this title

Synopsis

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 theclustering 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.

About the Author

Daniel Zelterman is professor in the department of biostatistics at Yale University. His research areas include computational statistics, models for discrete valued data, and the design of clinical trials in cancer studies. In his spare time he plays oboe and bassoon in amateur orchestral groups and has backpacked hundreds of miles of the Appalachian Trail.