Angielski
Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary.New to this edition are chapters devoted to longitudinal studies and the clustering of large data. This book is an excellent resources for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.
