Pragmatic and Adaptable Textbook Meets the Needs of Students and
Instructors from Diverse Fields
Numerical analysis is a core subject in data science and an essential
tool for applied mathematicians, engineers, and physical and biological
scientists. This updated and expanded edition of Numerical Analysis for
Applied Science follows the tradition of its precursor by providing a
modern, flexible approach to the theory and practical applications of
the field. As before, the authors emphasize the motivation,
construction, and practical considerations before presenting rigorous
theoretical analysis. This approach allows instructors to adapt the
textbook to a spectrum of uses, ranging from one-semester,
methods-oriented courses to multi-semester theoretical courses.
The book includes an expanded first chapter reviewing useful tools from
analysis and linear algebra. Subsequent chapters include clearly
structured expositions covering the motivation, practical
considerations, and theory for each class of methods. The book includes
over 250 problems exploring practical and theoretical questions and 32
pseudocodes to help students implement the methods. Other notable
features include:
- A preface providing advice for instructors on using the text for a
single semester course or multiple-semester sequence of courses
- Discussion of topics covered infrequently by other texts at this
level, such as multidimensional interpolation, quasi-Newton methods in
several variables, multigrid methods, preconditioned
conjugate-gradient methods, finite-difference methods for partial
differential equations, and an introduction to finite-element theory
- New topics and expanded treatment of existing topics to address
developments in the field since publication of the first edition
- More than twice as many computational and theoretical exercises as the
first edition.
Numerical Analysis for Applied Science, Second Edition provides an
excellent foundation for graduate and advanced undergraduate courses in
numerical methods and numerical analysis. It is also an accessible
introduction to the subject for students pursuing independent study in
applied mathematics, engineering, and the physical and life sciences and
a valuable reference for professionals in these areas.
