"... a systematic, well-written text... there is muchpractical wisdom in this book that is hard to find elsewhere. Itbelongs in serious data analysts' libraries...„ (IIETransactions-Quality and Reliability Engineering, November2005)
“... extends univariate procedures... to analogous multivariatetechniques involving several dependent variables...„ (SciTechBook News, Vol. 26, No. 2, June 2002)
“... a practitioner who wants to carry out multivariatetechniques in applied work and to interpret the results must havethis book...„ (Technometrics, Vol. 45, No. 1, February2003)
“... I have not found a better text for a masters-level class inmultivariate methods.„ (Journal of the American StatisticalAssociation, March 2003)
“This book strikes a nice balance between meeting the needs ofstatistics majors and students in other fields. The discussion ofeach multivariate technique is straightforward and quitecomprehensive. This textbook is likely to become a useful referencefor students in their future work.„ (Journal of the AmericanStatistical Association)
“In this well-written and interesting book, Rencher has done agreat job in presenting intuitive and innovative explanations ofsome of the otherwise difficult concepts.„ (CHOICE)
“This book is excellent for an introductory course inmultivariate analysis for students with minimal background inmathematics and statistics.„ (Technometrics)
“Excellent introduction to standard topics in multivariateanalysis." (American Mathematical Monthly)
Methods of Multivariate Analysis
von Alvin C. RencherWhen measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the jointperformance of such variables and to determine the effect of eachvariable in the presence of the others. The Second Edition of AlvinRencher's Methods of Multivariate Analysis provides studentsof all statistical backgrounds with both the fundamental and moresophisticated skills necessary to master the discipline.
To illustrate multivariate applications, the author providesexamples and exercises based on fifty-nine real data sets from awide variety of scientific fields. Rencher takes a „methods“approach to his subject, with an emphasis on how students andpractitioners can employ multivariate analysis in real-lifesituations. The Second Edition contains revised and updatedchapters from the critically acclaimed First Edition as well asbrand-new chapters on:
* Cluster analysis
* Multidimensional scaling
* Correspondence analysis
* Biplots
Each chapter contains exercises, with corresponding answers andhints in the appendix, providing students the opportunity to testand extend their understanding of the subject. Methods ofMultivariate Analysis provides an authoritative reference forstatistics students as well as for practicing scientists andclinicians.
