Basic Linear Algebra by Andrew Baker
About this book :-
This is an easy-to-understand book that teaches the basics of linear algebra, like vectors, matrices, systems of equations, determinants, and eigenvalues. It starts with simple ideas and slowly moves to more complicated ones. The book has lots of examples and practice problems to help you learn. The book is perfect for undergraduate students or anyone looking to get a solid grasp of linear algebra, with just the right mix of theory and practical applications."
It cover basic ideas and techniques of Linear Algebra that are applicable in many subjects including the physical and chemical sciences, statistics as well as other parts of mathematics. The notes end by discussing eigenvalues and eigenvectors which play a role in the theory of diagonalisation of square matrices, as well as many applications of linear algebra such as in geometry, differential equations and physics.
There are some assumptions that the reader will already have met vectors in 2 and 3-dimensional contexts, and has familiarity with their algebraic and geometric aspects. Basic algebraic theory of matrices is also assumed, as well as the solution of systems of linear equations using Gaussian elimination and row reduction of matrices. Thus the notes are suitable for a secondary course on the subject, building on existing foundations.
Book Detail :-
Title:
Basic Linear Algebra by Andrew Baker
Publisher:
University of Glasgow
Year:
2008
Pages:
73
Type:
PDF
Language:
English
ISBN-10 #:
N\A
ISBN-13 #:
N\A
License:
Linked Content Owned by Author
Amazon:
Amazon
About Author :-
The author
Andrew Baker
is Professor at School of Mathematics & Statistics, University of Glasgow, Scotland, UK. He is a respected math educator known for his clear and approachable teaching style. His main research area is Algebraic Topology, Galois Theory and Algebraic Geometry. He has a knack for making complex topics like linear algebra easier to understand, which shows in his book.
Book Contents :-
1. Vector Spaces and Subspaces
2. Spanning Sequences, Linear Independence and Bases
3. Linear Transformations
4. Determinants
5. Eigenvalues and Eigenvectors
A. Complex Solutions of Linear Ordinary Differential Equations
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