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Friday, May 1, 2020 | History

9 edition of Linear algebra for social sciences found in the catalog.

Linear algebra for social sciences

Menahem E. Yaari

Linear algebra for social sciences

  • 48 Want to read
  • 31 Currently reading

Published by Prentice-Hall in Englewood Cliffs, N.J .
Written in English

    Subjects:
  • Algebras, Linear

  • Edition Notes

    Statement[by] Menahem E. Yaari.
    SeriesPrentice-Hall series in mathematical economics
    Classifications
    LC ClassificationsQA251 .Y33
    The Physical Object
    Paginationxiv, 174 p.
    Number of Pages174
    ID Numbers
    Open LibraryOL5445616M
    ISBN 100135368391
    LC Control Number73117207


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Linear algebra for social sciences by Menahem E. Yaari Download PDF EPUB FB2

The book covers less mathematics than a typical text on applied linear algebra. We use only one theoretical concept from linear algebra, linear independence, and only one computational tool, the QR factorization; our approach to most applica-tions relies on only one method, least squares (or some extension).

In this sense. Additional Physical Format: Online version: Yaari, Menahem E. Linear algebra for social sciences. Englewood Cliffs, N.J., Prentice-Hall [] (OCoLC) A First Course in Linear Algebra is an introductory textbook aimed at college-level sophomores and juniors.

Typically students will have taken calculus, but it is not a prerequisite. The book begins with systems of linear equations, then covers matrix algebra, before taking up finite-dimensional vector spaces in full generality.

The final chapter covers matrix representations of /5(11). A college (or advanced high school) level text dealing with the basic principles of matrix and linear algebra. It covers solving systems of linear equations, matrix arithmetic, the determinant, eigenvalues, and linear transformations.

Numerous examples are given within the easy to read text. This third edition corrects several errors in the text and updates the font faces.4/5(1). The language and concepts of matrix theory and, more generally, of linear algebra have come into widespread usage in the social and natural sciences, computer science, and statistics.

In addition, linear algebra continues to be of great importance in modern treatments of geometry and by: 4. The book is distinguished by a step-by-step exposition that allows the reader to grasp quickly and fully the principles of linear algebra. All of the examples used to illustrate the text are drawn from the social sciences, enabling the reader to relate the subject to concrete problems in his : Gordon Mills.

Linear Algebra for Computational Sciences and Engineering. Authors: Neri, Ferrante This book presents the main concepts of linear algebra from the viewpoint of applied scientists such as computer scientists and engineers, without compromising on mathematical rigor. Based on the idea that computational scientists and engineers need, in both Brand: Springer International Publishing.

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We also acknowledge previous National Science Foundation support under grant numbers. Linear maps are mappings between vector spaces that preserve the vector-space structure.

Given two vector spaces V and W over a field F, a linear map (also called, in some contexts, linear transformation or linear mapping) is a map: → that is compatible with addition and scalar multiplication, that is (+) = + (), = ()for any vectors u,v in V and scalar a in F.

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João Filipe Queiro. No headers. This text, originally by K. Kuttler, has been redesigned by the Lyryx editorial team as a first course in linear algebra for science and engineering students who have an understanding of basic algebra.

All major topics of linear algebra are available in detail, as well as proofs of important theorems. Course description.

This course covers the following topics: solving systems of linear equations; matrices and linear transformations; image and kernel of a linear transformation; matrices and coordinates relative to different bases; determinants; eigenvalues and eigenvectors; discrete and continuous dynamical systems; least-squares approximation; applications, differential.

Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space.

Problems with hints and answers. Linear algebra moves steadily to n vectors in m-dimensional space. We still want combinations of the columns (in the column space). We still get m equations to produce b (one for each row). Those equations may or may not have a solution.

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