This textbook is intended to introduce advanced undergraduate and early-career graduate students to the field of numerical analysis. This field pertains to the design, analysis, and implementation of algorithms for the approximate solution of mathematical problems that arise in applications spanning science and engineering, and are not practical to solve using analytical techniques such as those taught in courses in calculus, linear algebra or differential equations.Topics covered include computer arithmetic, error analysis, solution of systems of linear equations, least squares problems, eigenvalue problems, nonlinear equations, optimization, polynomial interpolation and approximation, numerical differentiation and integration, ordinary differential equations, and partial differential equations. For each problem considered, the presentation includes the derivation of solution techniques, analysis of their efficiency, accuracy and robustness, and details of their implementation, illustrated through the Python programming language.This text is suitable for a year-long sequence in numerical analysis, and can also be used for a one-semester course in numerical linear algebra.
Customers who place a standing order for the Tests in Print series or the Mental Measurements Yearbook series will receive a 10% discount on every volume. To place your standing order, please call 1-800-848-6224 (in the U.S.) or 919-966-7449 (outside the U.S.). The Mental Measurements Yearbooks are widely regarded as essential references for users and developers of tests. Each yearbook contains reviews of commercially available tests published or revised since the previous edition. A biennial publication schedule for yearbooks and supplements was introduced in 1988 to facilitate access to test evaluation information and better meet the needs of test consumers. The Supplement to the Twelfth Mental Measurements Yearbook contains original reviews of tests published or revised since the 1995 edition of the Mental Measurements Yearbook. Tests are listed in alphabetical order for easy reference. Indexes of titles, classified subjects, names, acronmys, and scores, as well as an index and a directory of publishers, are included. A helpful indexing system integrating references across Buros Institute publications is also provided.
This textbook introduces advanced undergraduate and early-career graduate students to the field of numerical analysis. This field pertains to the design, analysis, and implementation of algorithms for the approximate solution of mathematical problems that arise in applications spanning science and engineering, and are not practical to solve using analytical techniques such as those taught in courses in calculus, linear algebra or differential equations. Topics covered include error analysis, computer arithmetic, solution of systems of linear equations, least squares problems, eigenvalue problems, polynomial interpolation and approximation, numerical differentiation and integration, nonlinear equations, optimization, ordinary differential equations, and partial differential equations. For each problem considered, the presentation includes the derivation of solution techniques, analysis of their efficiency, accuracy and robustness, and details of their implementation, illustrated through the MATLAB programming language. This text is suitable for a year-long sequence in numerical analysis, and can also be used for a one-semester course in numerical linear algebra.
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