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Multivariate Analysis (Probability and Mathematical Statistics) - Hardcover

 
9780124712515: Multivariate Analysis (Probability and Mathematical Statistics)
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This long-awaited revision combines a theoretical and data analytic approach to the subject, whilst emphasising modern developments in the field. Topics covered include econometrics, principal component analysis, factor analysis, canonical correlation analysis, discriminate analysis, cluster analysis, multi-dimensional scaling and directional data. Several methods of presentation, which helped make the first edition popular with professional statisticians and students alike, are used. For example, the data matrix is emphasised throughout, and density-free approach is given to normal theory. Tests are constructed using the likelihood ratio principle and the union intersection principle, and graphical methods are used in explanation. This work combines theoretical and data analytic approach. Appendices provide background of matrix algebra, univariate statistics and statistical tables. It offers a concise presentation.

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Multivariate Analysis deals with observations on more than one variable where there is some inherent interdependence between variables. Most available books on the subject concentrate on either the theoretical or the data analytic approach. This book not only combines theses two approaches but also emphasizes modern developments, so, although primarily designed as a textbook for final year undergraduates and postgraduate students in mathematics and statistics, certain of the sections will commend themselves to research workers.
Broadly speaking the first half of the book contains direct extensions of univariate ideas and techniques, including exploratory data analysis, distribution theory and problems of inference. The remaining chapters concentrate on specifically multivariate problems which have no meaningful analogues in the univariate case. Topics covered include econometrics, principal component analysis, factor analysis, canonical correlation analysis, discriminate analysis, cluster analysis, multi-dimensional scaling and directional data.
Several new methods of presentation are used, for example, the data matrix is emphasized throughout, and density-free approach is given to normal theory, tests are constructed using the likelihood ratio principle and the union intersection principle, and graphical methods are used in explanation.
The reader is assumed to have a basic knowledge of mathematical statistics at an undergraduate level together with an elementary understanding of linear algebra. There are, however, appendices which provide a sufficient background of matrix algebra, a summary of univariate statistics and some statistical tables.
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Edited by K. V. Mardia

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Other Popular Editions of the Same Title

9780124712522: Multivariate Analysis (Probability and Mathematical Statistics)

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ISBN 10:  0124712525 ISBN 13:  9780124712522
Publisher: Academic Press, 1980
Softcover

  • 9780124712508: Multivariate Analysis

    Academ..., 1979
    Hardcover

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