Posted by **arundhati** at Dec. 18, 2017

2003 | ISBN-10: 0471391042, 047012069X | 704 pages | PDF | 8 MB

Posted by **AvaxGenius** at Oct. 12, 2017

English | PDF,EPUB | 2017 | 664 Pages | ISBN : 3319648667 | 12.91 MB

This textbook for graduate and advanced undergraduate students presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra. Matrix algebra is one of the most important areas of mathematics in data science and in statistical theory, and the second edition of this very popular textbook provides essential updates and comprehensive coverage on critical topics in mathematics in data science and in statistical theory.

Posted by **AvaxGenius** at Oct. 3, 2018

English | True PDF | 2007 | 536 Pages | ISBN : 0387708723 | 4.85 MB

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. The first part of this book presents the relevant aspects of the theory of matrix algebra for applications in statistics. This part begins with the fundamental concepts of vectors and vector spaces, next covers the basic algebraic properties of matrices, then describes the analytic properties of vectors and matrices in the multivariate calculus, and finally discusses operations on matrices in solutions of linear systems and in eigenanalysis. This part is essentially self-contained.

Posted by **hill0** at Feb. 3, 2019

(Cambridge Series in Statistical and Probabilistic Mathematics)

by Roman Vershynin

English | 2018 | ISBN: 1108415199 | 300 Pages | PDF | 5 MB

Posted by **Underaglassmoon** at Nov. 6, 2017

Cambridge | English | Oct 2017 | ISBN-10: 1107096006 | 480 pages | PDF | 7.10 mb

by Alan D. Chave (Author)

Posted by **roxul** at April 5, 2018

English | 7 Aug. 2016 | ISBN: 3319283154 | 298 Pages | EPUB | 3 MB

Posted by **AvaxGenius** at Aug. 31, 2018

English | EPUB | 2016 | 285 Pages | ISBN : 3319283154 | 2.75 MB

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.

Posted by **AvaxGenius** at July 9, 2018

English | EPUB | 2016 | 285 Pages | ISBN : 3319283154 | 2.75 MB

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.

Posted by **AlenMiler** at Feb. 3, 2019

English | March 12, 2007 | ISBN: 0470854952 | 348 pages | PDF | 3.38 Mb

Posted by **AvaxGenius** at July 27, 2018

English | PDF,EPUB | 2018 | 283 Pages | ISBN : 3319937723 | 17.69 MB

This book was written to serve as a graduate-level textbook for special topics classes in mathematics, statistics, and economics, to introduce these topics to other researchers, and for use in short courses. It is an introduction to the theory of majorization and related notions, and contains detailed material on economic applications of majorization and the Lorenz order, investigating the theoretical aspects of these two interrelated orderings.