Topics and features:

• Describes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves
• Discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations
• Presents tools from vector and matrix algebra in the appendices, together with further information on continuity
• Includes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation (NEW)
• Contains experiments, exercises, definitions, and propositions throughout the text
• Supplies programming examples in Python, in addition to MATLAB (NEW)
• Provides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material

Addressing the core needs of computer science students and researchers, this clearly written textbook is an essential resource for undergraduate-level courses on numerical analysis, and an ideal self-study tool for professionals seeking to enhance their analysis skills.

Dr. Michael Oberguggenberger is a professor in the Unit of Engineering Mathematics at the University of Innsbruck, Austria. Dr. Alexander Ostermann is a professor in the Department of Mathematics at the University of Innsbruck, Austria.