Introduction to Scientific Computing and Data Analysis

This textbook provides and introduction to numerical computing and its applications in science and engineering.  The topics covered include those usually found in an introductory course, as well as those that arise in data analysis.  This includes optimization and regression based methods using a singular value decomposition.  The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science.  The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.  The MATLAB codes used to produce most of the figures and data tables in the text are available on the author’s website and SpringerLink.

Table of Contents

Chapter 1 Introduction to Scientific Computing
Chapter 2 Solving A Nonlinear Equation
Chapter 3 Matrix Equations
Chapter 4 Eigenvalue Problems
Chapter 5 Interpolation
Chapter 6 Numerical Integration
Chapter 7 Initial Value Problems
Chapter 8 Optimization
Chapter 9 Data Analysis
Appendix A Taylor’s Theorem
Appendix B B-Splines
Appendix C Summary Tables