Matrices for statistics
Author(s)
Bibliographic Information
Matrices for statistics
(Oxford science publications)
Clarendon Press, 1991, c1986
- : pbk
Available at 24 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
"First published 1986. First published in paperback (with corrections) 1991" -- t.p. verso
Description and Table of Contents
Description
Multiple regression, linear modelling, and multivariate analysis are among the most useful statistical methods for the elucidation of complicated data, and all of them are most easily explained in matrix terms. Anyone concerned with the analysis of data needs to be familiar with these methods and a knowledge of matrices is essential in order to understand the literature in which they are described. This knowledge must include some advanced topics, but can do without much of the material covered by general textbooks of matrix algebra. This book is intended to cover the necessary ground as briefly as possible. Only the simplest of basic mathematics is used, and the book should be accessible to statisticians, engineers, biologists, and social scientists as well as those with a specifically mathematical background. Numerical methods for matrices are described and the book contains a set of algorithms to make such methods generally available. This book is intended for students of statistics and their lecturers; a wide range of users of statistics from all disciplines.
Table of Contents
- Introducing matrices
- determinants
- inverse matrices
- linear independence and rank
- simultaneous equations and generalized invereses
- linear spaces
- quadratic forms and eigensystems
- matrix calculations.
by "Nielsen BookData"