Using R With Multivariate Statistics
by Randall E. Schumacker
- New Delhi Sage 2016
- xxi, 383 pages; Illustrations: 25 cm.
1. Introduction and Overview Background
Persons of Interest
Factors Affecting Statistics
R Software
Web Resources
References
2. Multivariate Statistics: Issues and Assumptions Issues
Assumptions
SPSS Check
Summary
Web Resources
References
3. Hotelling’s T2 : A Two-Group Multivariate Analysis Overview
Assumptions
Univariate Versus Multivariate Hypothesis
Practical Examples Using R
Power and Effect Size
Reporting and Interpreting
Summary
Exercises
Web Resources
References
4. Multivariate Analysis of Variance MANOVA Assumptions
MANOVA Example: One-Way Design
MANOVA Example: Factorial Design
Effect Size
Reporting and Interpreting
Summary
Exercises
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.