Methods of Multivariate Analysis / Wiley Series in Probability and Statistics (PDF)
(Sprache: Englisch)
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...
"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...
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Produktinformationen zu „Methods of Multivariate Analysis / Wiley Series in Probability and Statistics (PDF)“
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:
* Confirmatory Factor Analysis
* Classification Trees
* Dynamic Graphics
* Transformations to Normality
* Prediction for Multivariate Multiple Regression
* Kronecker Products and Vec Notation
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.
"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:
* Confirmatory Factor Analysis
* Classification Trees
* Dynamic Graphics
* Transformations to Normality
* Prediction for Multivariate Multiple Regression
* Kronecker Products and Vec Notation
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.
Autoren-Porträt von Alvin C. Rencher, William F. Christensen
ALVIN C. RENCHER is Professor Emeritus in the Departmentof Statistics at Brigham Young University. A Fellow of the American
Statistical Association, he is the author of Linear Models in
Statistics, Second Edition and Multivariate Statistical
Inference and Applications, both published by Wiley.
WILLIAM F. CHRISTENSEN is Professor in the Department of
Statistics at Brigham Young University. He has been published
extensively in his areas of research interest, which include
multivariate analysis, resampling methods, and spatial and
environmental statistics.
Bibliographische Angaben
- Autoren: Alvin C. Rencher , William F. Christensen
- 2012, 3. Auflage, 800 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118391659
- ISBN-13: 9781118391655
- Erscheinungsdatum: 23.07.2012
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- Größe: 28 MB
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Sprache:
Englisch
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