Text
An Introduction to Multivariate Statistical Analysis 3rd ed
This third edition is a wonderful textbook for graduate students studying statistics or professional statisticians interested in a thorough introduction to the mathematical theory underlying many common multivariate statistical methods. However, if you are a laboratory scientist lacking a strong mathematical background, this book is not for you. The author earned his PhD in mathematics at Princeton in 1945 and has been an influential figure in the statistical field for many decades. In addition to this book, he is also the author of The Statistical Analysis of Time Series. The first edition of An Introduction to Multivariate Statistical Analysis was derived from lecture notes used in a two-semester sequence of graduate courses given at Columbia University. Published in 1958, it was one of the early books on multivariate statistical analysis, along with M.G. Kendall?s monograph, A Course in Multivariate Analysis, published in 1957, and S.N. Roy?s Some Aspects of Multivariate Analysis, published the same year. It was intended for individuals interested in a ?mathematically rigorous development? of the statistical methods. A background in univariate statistical theory and matrix algebra is a prerequisite. This latest edition retains its focus on mathematical theory but has been updated to include recent theoretical developments. The book contains a comprehensive reference list. Of the 446 references, 48 have been published since 1984, when the second edition of the text appeared, and 167 were published before 1958. Many of the classic multivariate statistical topics are covered, including the multivariate normal distribution, multivariate classification, multivariate analysis of variance, principal components, canonical correlation, and factor analysis. Unfortunately, computer software for performing multivariate analysis is not addressed. Likewise, multivariate data analysis methods that rely on computer-intensive techniques are not covered. The book follows the theorem/proof format common in many mathematics texts. Most problems appearing at the end of each chapter also request a proof. Only three actual data sets appear in the entire book, one is introduced in the text, and the other two are presented in problems at the end of a chapter. All of the data appearing in the book are from publications before 1958. Topics that some laboratorians might look for in a book with the word ?multivariate? in the title that are not covered in this book include cluster analysis; various forms of multiple regression analysis, including multiple linear regression, logistic regression, and proportional hazards regression (survival analysis); and methods for the graphic presentation of multivariate data. If you are looking for a text that covers the mathematical theory of multivariate statistical analysis, this book will serve you well, but if you are looking for a text that addresses how to analyze and interpret multivariate data, then a text on multivariate data analysis (as opposed to multivariate statistical analysis) such as Computer-Aided Multivariate Analysis by Afifi, May, and Clark, or Applied Multivariate Data Analysis by Everitt and Dunn would probably be a better choice.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| Tan 519. 535 And i | PSB lt.dasar - Pascasarjana | 1 |
| Penerbit | New York John Wiley & Sons., 2003 |
|---|---|
| Edisi | - |
| Subjek | Multivariate analysis |
| ISBN/ISSN | - |
| Klasifikasi | - |
| Deskripsi Fisik | - |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |