Basic textbook covers theory of matrices and its applications to systems of linear equations and related topics such as determinants, eigenvalues, and differential equations. Includes numerous exercises.
Matrices and linear transformations are presented as two sides of the same coin, with their connection motivating inquiry throughout the book.
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
The book also covers statistics with applications to design and statistical process controls.
Advanced undergraduate and first-year graduate students have long regarded this text as one of the best available works on matrix theory in the context of modern algebra.
The authors show the many topics and tools encompassed by modern linear algebra to emphasize its relationship to other areas of mathematics. The text is intended for advanced undergraduate students.
Cohen, E.L. and R.N. Kesarwani, Linear Algebra, Kendall Hunt, Dubuque (Indiana), 1984. Coulson, A.E., Introduction to Matrices, Longman, London, 1965. Crouch, T., Matrix Methods Applied to Engineering Rigid Body Mechanics, ...
A stand-alone textbook in matrix algebra for econometricians and statisticians - advanced undergraduates, postgraduates and teachers.
Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics.
Undergraduate-level introduction to linear algebra and matrix theory.
Intended for a serious first course or a second course, this textbook will carry students beyond eigenvalues and eigenvectors to the classification of bilinear forms, to normal matrices, to spectral decompositions, and to the Jordan form.