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Applied Multivariate Statistics with R Second Edition 2022 [Pehme köide]

  • Formaat: Paperback / softback, 463 pages, kõrgus x laius: 235x155 mm, kaal: 735 g, 158 Illustrations, color; 14 Illustrations, black and white; XIX, 463 p. 172 illus., 158 illus. in color., 1 Paperback / softback
  • Sari: Statistics for Biology and Health
  • Ilmumisaeg: 21-Jan-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031130073
  • ISBN-13: 9783031130076
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  • Formaat: Paperback / softback, 463 pages, kõrgus x laius: 235x155 mm, kaal: 735 g, 158 Illustrations, color; 14 Illustrations, black and white; XIX, 463 p. 172 illus., 158 illus. in color., 1 Paperback / softback
  • Sari: Statistics for Biology and Health
  • Ilmumisaeg: 21-Jan-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031130073
  • ISBN-13: 9783031130076
Teised raamatud teemal:

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.

Chapter
1. Introduction.
Chapter
2. Elements of R.
Chapter
3.
Graphical Displays.
Chapter
4. Basic Linear Algebra.
Chapter
5. The
Univariate Normal Distribution.
Chapter
6. Bivariate Normal Distribution.-
Chapter
7. Multivariate Normal Distribution.
Chapter
8. Factor Methods.-
Chapter
9. Multivariate Linear Regression.
Chapter
10. Discrimination and
Classification.
Chapter
11. Clustering Methods.
Chapter
12. Basic Models
for Longitudinal Data.
Chapter
13. Time Series Models.
Chapter
14. Other
Useful Methods.
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.