ABSTRACT

This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.

This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.

•Where is the method applied?
•How is the method developed?
•How is the method implemented?
•How well does the method work?

The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

chapter 1|8 pages

An Overview of Scientific Computing

chapter 2|16 pages

Taylor's Theorem

chapter 3|18 pages

Roundoff Errors and Error Propagation

chapter 4|42 pages

Direct Methods for Linear Systems

chapter 5|46 pages

Root Finding for Nonlinear Equations

chapter 6|52 pages

Interpolation

chapter 7|42 pages

Numerical Integration

chapter 8|12 pages

Numerical Differentiation

chapter 10|16 pages

Basic Iterative Methods for Linear Systems

chapter 11|18 pages

Discrete Least Squares Problems

chapter 12|10 pages

Monte Carlo Methods and Parallel Computing