This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
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.
"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.
For graduate and upper-level undergraduate marketing research courses.For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.
Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications.
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, ...
Turk, M.A., 22, 704 Uitdenbogerd, A., 476, 704 Ultsch, A., 435, 704 Uthumsamy, R., 16, 679 Valdivia-Granda, W.A., 43, ... 36, 705 Williams, C.K.I., 613, 629, 705 Williams, R.J., 365 Williams, W.T., 420, 692 Wilson, R., 146, 680 Wishart, ...
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
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis.
This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms.
The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems.