Overview
- Approach to multivariate statistics for diverse applications that does not require advanced degree in statistics
- R is used throughout for statistical analyses and computing, but prior experience with R is not necessary
- Contains exercises, full code to carry out the engaging examples, and selected solutions included in an appendix
Part of the book series: Statistics for Biology and Health (SBH)
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Table of contents (13 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor 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. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary.
Reviews
“This book is so clearly explained with R code throughout that it could be used as a self-learning text for an applied multivariate course and should be assigned as a selflearning adjunct assignment for a graduate level theoretical multivariate course. The real-word examples are page turners and ubiquitous use of color and fancy graphs easily explained make this usually dry topic an exciting one.” (Donna Pauler Ankerst, Biometrics, Vol. 73 (1), March, 2017)
“This book demonstrates the process and outcomes for a wide array of multivariate statistical applications using program R. … The chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. This book is strongly recommended for graduate-level statistics practitioners.” (Hemang B. Panchal, Doody’s Book Reviews, December, 2015)
Authors and Affiliations
About the author
Daniel Zelterman, PhD, 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.
Bibliographic Information
Book Title: Applied Multivariate Statistics with R
Authors: Daniel Zelterman
Series Title: Statistics for Biology and Health
DOI: https://doi.org/10.1007/978-3-319-14093-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2015
eBook ISBN: 978-3-319-14093-3Published: 03 August 2015
Series ISSN: 1431-8776
Series E-ISSN: 2197-5671
Edition Number: 1
Number of Pages: XVI, 393
Number of Illustrations: 13 b/w illustrations, 108 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Biostatistics, Epidemiology, Bioinformatics, Systems Biology