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Matrix Theory and Linear Algebra by Peter Selinger




Matrix Theory and Linear Algebra - Table of Contents

  • 1. Systems of Linear Equations
  • 2. Vectors in Rn
  • 3. Lines and Planes in Rn
  • 4. Matrices
  • 5. Spans, Linear Independence, and Bases in Rn
  • 6. Linear Transformations in Rn
  • 7. Determinants
  • 8. Eigenvalues, Eigenvectors, and Diagonalization
  • 9. Vector Spaces
  • 10. Linear Transformation of Vector Spaces
  • 11. Inner Product Spaces
  • 12. Appendix A: Complex Numbers

What You Will Learn in Matrix Theory and Linear Algebra

Matrix Theory and Linear Algebra by Peter Selinger is a comprehensive open-access undergraduate textbook designed for students in mathematics, computer science, data science, and engineering. Widely recognized as a foundational text in matrix theory and linear algebra, this volume balances structural theory with concrete computational techniques.

The textbook systematically covers systems of linear equations, Gaussian elimination, matrix algebra, vector spaces, linear independence, determinants, eigenvalues, eigenvectors, and linear transformations. Studying the matrix theory and linear algebra Peter Selinger pdf provides rigorous proofs and practical numerical methods that build essential problem-solving skills.

Praised by university educators for its logical exposition and clear pedagogical structure, this text bridges introductory mathematics with advanced matrix computations. Mastering matrix theory and linear algebra equips students with core analytical tools required for higher mathematics, data analysis, and engineering applications.

Book Details & Specifications

Title: Matrix Theory and Linear Algebra by Peter Selinger
Publisher: Open Educational Text
Year: 1905
Pages: 561
Type: PDF
Language: English
ISBN-10 #: N\A
ISBN-13 #: N\A
License: CC BY 4.0
Amazon: Amazon

About the Author: Peter Selinger

The author Peter Selinger is Professor of Mathematics and Computer Science at Dalhousie University, Nova Scotia, Canada, renowned for his research in quantum computing, programming language theory, and category theory.

His open educational textbooks, particularly in matrix theory and linear algebra, are globally utilized by universities and independent learners.


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