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Tidsskrift
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Description
Summary: Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.
Content
Latest edition, e-bogI. GETTING STARTED -- 1. Aspects of Multivariate Analysis -- 2. Sample Geometry and Random Sampling -- 3. Matrix Algebra and Random Vectors -- 4. The Multivariate Normal Distribution -- II. INFERENCES ABOUT MULTIVARIATE MEANS AND LINEAR MODELS -- 5. Inferences About a Mean Vector -- 6. Comparisons of Several Multivariate Means -- 7. Multivariate Linear Regression Models -- III. ANALYSIS OF A COVARIANCE STRUCTURE -- 8. Principal Components -- 9. Factor Analysis and Inference for Structured Covariance Matrices -- 10. Canonical Correlation Analysis -- IV. CLASSIFICATION AND GROUPING TECHNIQUES -- 11. Discrimination and Classification -- 12. Clustering, Distance Methods and Ordination -- Appendix -- Data Index -- Subject Index
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