Applied multivariate statistics with R /

Applied multivariate statistics with R /

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Bibliographic Details
Author / Creator:	Zelterman, Daniel, author.
Imprint:	Cham : Springer, [2015] ©2015
Description:	1 online resource (xvi, 393 pages) : illustrations (some color), portraits.
Language:	English
Series:	Statistics for biology and health, 2197-5671 Statistics for biology and health.
Subject:	Multivariate analysis. Mathematical statistics. R (Computer program language) Mathematical statistics. Multivariate analysis. R (Computer program language)
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11095588

Hidden Bibliographic Details
ISBN:	9783319140933 3319140930 9783319140926 3319140922
Digital file characteristics:	text file PDF
Notes:	Includes bibliographical references (pages 375-379) and index. Online resource; title from PDF title page (EBSCO, viewed August 5, 2015).
Summary:	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.℗ℓ.
Other form:	Print version: Zelterman, Daniel. Applied multivariate statistics with R. Cham : Springer, 2015 9783319140926
Standard no.:	10.1007/978-3-319-14093-3

Table of Contents:

Introduction.- Elements of R
Graphical Displays
Basic Linear Algebra
The Univariate Normal Distribution
Bivariate Normal Distribution
Multivariate Normal Distribution
Factor Methods
Multivariate Linear Regression
Discrimination and Classification
Clustering
Time Series Models
Other Useful Methods
References
Appendix
Selected Solutions
Index.