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Using R With Multivariate Statistics
First Edition
- Randall E. Schumacker - University of Alabama, Tuscaloosa, USA
Other Titles in:
Quantitative/Statistical Research (General)
Quantitative/Statistical Research (General)
August 2015 | 408 pages | SAGE Publications, Inc
Using R with Multivariate Statistics is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.
Available with Perusall—an eBook that makes it easier to prepare for class
Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Available with Perusall—an eBook that makes it easier to prepare for class
Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Preface
Acknowledgments
About the Author
1. Introduction and Overview
2. Multivariate Statistics: Issues and Assumptions
3. Hotelling’s T2 : A Two-Group Multivariate Analysis
4. Multivariate Analysis of Variance
5. Multivariate Analysis of Covariance
6. Multivariate Repeated Measures
7. Discriminant Analysis
8. Canonical Correlation
9. Exploratory Factor Analysis
10. Principal Components Analysis
11. Multidimensional Scaling
12. Structural Equation Modeling
Statistical Tables
Chapter Answers
R Installation and Usage
R Packages, Functions, Data Sets, and Script Files
Index
Supplements
“This book is not only an excellent introductory resource of multivariate statistics using R, but also provides a complete coverage of multivariate statistics. I really love this book and look forward to using it for my stats courses.”
“The use of the programming language R in a meaningful way is a great strength of this book, as is the associated emphasis on matrix algebra. Also, the addition of brief biographies of key statisticians makes this book more interesting. Finally, the range and scope of techniques that are presented is impressive.”
“The text is down-to-earth and practical, with a straightforward approach to communicating a set of procedures for analyzing data.”
“[…]I found the directions very clear and was able to run the syntax and get the output very easily.”
I adopted this book as the supplementary book to my course. This book, in my opinion, has the advantage of being technical (compared to Filed's books) which makes it more attractive to stronger students who want to have deeper understanding.
Educational Psychology , University Of Saskatchewan
September 10, 2015
