Offering an applications-oriented approach which focuses on the use of each technique rather than its mathematical derivation, this textbook introduces a six-step framework for organising and discussing multivariate data analysis techniques.
"This is an ideal text for advanced undergraduate and graduate courses across the social sciences. Practitioners who need to refresh their knowledge of MDA will also find this an invaluable resource."--BOOK JACKET.
The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field.
With extensive exercises following every chapter, the book is a valuable resource for students on applied statistics courses and for applied researchers in many disciplines.
This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms.
Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify ...
MULTIVARIATE DATA ANALYSIS.
The Third Edition features new or more extensive coverage of: Patterns of Dependence and Graphical Models–a new chapter Measures of correlation and tests of independence Reduced rank regression, including the limited-information maximum ...
We first find the convex hull of the data (i.e., the observations defining the convex hull) using the following R code: R> (hull with(USairpollution, ...
Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results.