Fr. 276.00

Introduction to Multivariate Statistical Analysis

Englisch · Fester Einband

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Informationen zum Autor Anderson wrote this book as a simple visual tool to make clear that while appearing normal, living with Chronic Fatigue is a life-changing and controlling disease with a complex combination and fluctuation of symptoms that cannot be seen. Adjusting to change, letting go of control, focusing on wellbeing, practicing yoga, and simply trusting and accepting what is has been a profound learning experience for Anderson. Klappentext Perfected over three editions and more than forty years, this field- and classroom-tested reference:* Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures.* Treats all the basic and important topics in multivariate statistics.* Adds two new chapters, along with a number of new sections.* Provides the most methodical, up-to-date information on MV statistics available. Zusammenfassung Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics. Inhaltsverzeichnis Preface to the Third Edition. Preface to the Second Edition. Preface to the First Edition. 1. Introduction. 2. The Multivariate Normal Distribution. 3. Estimation of the Mean Vector and the Covariance Matrix. 4. The Distributions and Uses of Sample Correlation Coefficients. 5. The Generalized T 2-Statistic. 6. Classification of Observations. 7. The Distribution of the Sample Covariance Matrix and the Sample Generalized Variance. 8. Testing the General Linear Hypothesis: Multivariate Analysis of Variance 9. Testing Independence of Sets of Variates. 10. Testing Hypotheses of Equality of Covariance Matrices and Equality of Mean Vectors and Covariance Matrices. 11. Principal Components. 12. Cononical Correlations and Cononical Variables. 13. The Distributions of Characteristic Roots and Vectors. 14. Factor Analysis. 15. Pattern of Dependence; Graphical Models. Appendix A: Matrix Theory. Appendix B: Tables. References. Index. ...

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