Applied Multivariate Statistics with R

✍ Scribed by Daniel Zelterman

• Publisher: Springer
• Year: 2015
• Tongue: English
• Leaves: 411
• Series: Statistics for Biology and Health
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xvi
Introduction....Pages 1-15
Elements of R ....Pages 17-53
Graphical Displays....Pages 55-87
Basic Linear Algebra....Pages 89-116
The Univariate Normal Distribution....Pages 117-150
Bivariate Normal Distribution....Pages 151-172
Multivariate Normal Distribution....Pages 173-205
Factor Methods....Pages 207-229
Multivariable Linear Regression....Pages 231-256
Discrimination and Classification....Pages 257-286
Clustering....Pages 287-313
Time Series Models....Pages 315-338
Other Useful Methods....Pages 339-360
Back Matter....Pages 361-393

✦ Subjects

Statistics for Life Sciences, Medicine, Health Sciences; Biostatistics; Epidemiology; Bioinformatics; Systems Biology