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Download Chapter 4 - A Sampling of Linear Models (17.2 MB)
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This book develops linear algebra around matrices. Vector spaces in the abstract are not considered, only vector spaces associated with matrices. This book puts problem solving and an intuitive treatment of theory first, with a proof-oriented approach intended to come in a second course, the same way that calculus is taught. The book's organization is straightforward: Chapter 1 has introductory linear models; Chapter 2 has the basics of matrix algebra; Chapter 3 develops different ways to solve a system of equations; Chapter 4 has applications, and Chapter 5 has vector-space theory associated with matrices and related topics such as pseudoinverses and orthogonalization. Many linear algebra textbooks start immediately with Gaussian elimination, before any matrix algebra. Here we first pose problems in Chapter 1, then develop a mathematical language for representing and recasting the problems in Chapter 2, and then look at ways to solve the problems in Chapter 3-four different solution methods are presented with an analysis of strengths and weaknesses of each.
Basix Custom Publishing
linear algebra, Markov chains, linear programming, economic input-output models, regression
Algebra | Mathematics
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Tucker, Alan, "Introduction to Linear Algebra: Models, Methods, and Theory" (1995). Department of Applied Mathematics & Statistics Faculty Books. 1.