The fifth edition of Numerical Methods for Engineers continues its tradition of excellence.

Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines.

The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods.

Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering.

Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.

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Part 1 Modeling, Computers, and Error Analysis 1 Mathematical Modeling and Engineering Problem Solving 2 Programming and Software 3 Approximations and Round-Off Errors 4 Truncation Errors and the Taylor Series

Part 2 Roots of Equations 5 Bracketing Methods 6 Open Methods 7 Roots of Polynomials 8 Case Studies: Roots of Equations

Part 3 Linear Algebraic Equations 9 Gauss Elimination 10 LU Decomposition and Matrix Inversion 11 Special Matrices and Gauss-Seidel 12 Case Studies: Linear Algebraic Equations

Part 4 Optimization 13 One-Dimensional Unconstrained Optimization 14 Multidimensional Unconstrained Optimization 15 Constrained Optimization 16 Case Studies: Optimization

Part 5 Curve Fitting 17 Least-Squares Regression 18 Interpolation 19 Fourier Approximation 20 Case Studies: Curve Fitting

Part 6 Numerical Differentiation and Integration 21 Newton-Cotes Integration Formulas 22 Integration of Equations 23 Numerical Differentiation 24 Case Studies: Numerical Integration and Differentiation

Part 7 Ordinary Differential Equations 25 Runge-Kutta Methods 26 Stiffness and Multistep Methods 27 Boundary-Value and Eigenvalue Problems 28 Case Studies: Ordinary Differential Equations

Part 8 Partial Differential Equations 29 Finite Difference: Elliptic Equations 30 Finite Difference: Parabolic Equations 31 Finite-Element Method 32 Case Studies: Partial Differential Equations

Appendix A The Fourier Series

Appendix B Getting Started with Matlab

Bibliography

Index