Researchers involved in the collection of scientific data often end up with multivariate systems. When several variables are simultaneously measured on the same experimental unity, they are usually correlated, and the pattern formed is often too difficult for the human mind to grasp. This text discusses in detail many proven techniques for finding the dimensionality of the pattern and unravelling the information contained in the complexity of variables. The book includes exercises and solutions as well as 41 data sets taken from various areas of application, such as engineering, manufacturing, medicine, social science and economics.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Praise for the Second Edition
"This book is a systematic, well–written, well–organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."
IIE Transactions
Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real–life situations.
This Third Edition continues to explore the key descriptive and inferential procedures that result from multivariate analysis. Following a brief overview of the topic, the book goes on to review the fundamentals of matrix algebra, sampling from multivariate populations, and the extension of common univariate statistical procedures (including t–tests, analysis of variance, and multiple regression) to analogous multivariate techniques that involve several dependent variables. The latter half of the book describes statistical tools that are uniquely multivariate in nature, including procedures for discriminating among groups, characterizing low–dimensional latent structure in high–dimensional data, identifying clusters in data, and graphically illustrating relationships in low–dimensional space. In addition, the authors explore a wealth of newly added topics, including:
New exercises have been added throughout the book, allowing readers to test their comprehension of the presented material. Detailed appendices provide partial solutions as well as supplemental tables, and an accompanying FTP site features the book′s data sets and related SAS® code.
Requiring only a basic background in statistics, Methods of Multivariate Analysis, Third Edition is an excellent book for courses on multivariate analysis and applied statistics at the upper–undergraduate and graduate levels. The book also serves as a valuable reference for both statisticians and researchers across a wide variety of disciplines.
" a systematic, well–written text there is much practical wisdom in this book that is hard to find elsewhere. It belongs in serious data analysts′ libraries " ( IIE Transactions–Quality and Reliability Engineering, November 2005)
"...extends univariate procedures...to analogous multivariate techniques involving several dependent variables..." (SciTech Book News, Vol. 26, No. 2, June 2002)
"...a practitioner who wants to carry out multivariate techniques in applied work and to interpret the results must have this book..." (Technometrics, Vol. 45, No. 1, February 2003)
"...I have not found a better text for a masters–level class in multivariate methods." (Journal of the American Statistical Association, March 2003)
"This book strikes a nice balance between meeting the needs of statistics majors and students in other fields. The discussion of each multivariate technique is straightforward and quite comprehensive. This textbook is likely to become a useful reference for students in their future work." (Journal of the American Statistical Association)
"In this well–written and interesting book, Rencher has done a great job in presenting intuitive and innovative explanations of some of the otherwise difficult concepts." (CHOICE)
"This book is excellent for an introductory course in multivariate analysis for students with minimal background in mathematics and statistics." (Technometrics)
"Excellent introduction to standard topics in multivariate analysis." (American Mathematical Monthly)
"...extends univariate procedures...to analogous multivariate techniques involving several dependent variables..." (SciTech Book News, Vol. 26, No. 2, June 2002)
"...a practitioner who wants to carry out multivariate techniques in applied work and to interpret the results must have this book..." (Technometrics, Vol. 45, No. 1, February 2003)
"...I have not found a better text for a masters–level class in multivariate methods." (Journal of the American Statistical Association, March 2003)
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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