Multivariate Statistical Inference is a 10-chapter text that covers the theoretical and applied aspects of multivariate analysis, specifically the multivariate normal distribution using the invariance approach.<br><br>Chapter I contains some special results regarding characteristic roots and vectors
Multivariate Statistical Analysis for Biologists
β Scribed by Hilary L. Seal
- Publisher
- Methuen
- Year
- 1964
- Tongue
- English
- Leaves
- 230
- Category
- Library
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
<p><p>This book presents recent non-asymptotic results for approximations in multivariate statistical analysis. The book is unique in its focus on results with the correct error structure for all the parameters involved. Firstly, it discusses the computable error bounds on correlation coefficients,
This is probably the best applied statistics book I have ever read. It is not one of the "for dummies" book, it does use some linear algebra and requires some knowledge of elementary statistics, but at the same time it is very clear and understandable. I think this is the only reasonable approach -
With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in a way that
<p>Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices. In medicine recorded observations of subjects in differ
<p>Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices. In medicine recorded observations of subjects in differ