Applied Multivariate Analysis:
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Bibliographic Details
Other Authors: Timm, Neil H. (Editor)
Format: Electronic eBook
Language:English
Published: New York, NY Springer New York 2002
Series:Springer Texts in Statistics
Subjects:
Online Access:Volltext
Item Description:Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to provide students and researchers with an introduction to statistical techniques for the analysis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous observations from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data analysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text
Physical Description:1 Online-Ressource (XXIV, 695 p)
ISBN:9780387227719
9780387953472
ISSN:1431-875X
DOI:10.1007/b98963

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