Scientific Computing

Rating:
Summary: A better book than the rest
Review: For a teaching book this is better than anyother book out on the market. It skims over the material, which makes it so the students don't get bored or overwhelmed by it. I have read books that were a lot more in depth about Algorithms Analysis espically the Knuth series, but that is too much for the introductionary course to Numerical Analysis and this book offers breadth and some depth when it comes time to deal with the complicated subject matter. This book recieves three stars, just because all the other books are worse.

Rating:
Summary: A Good Introductory Survey
Review: This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

Rating:
Summary: Excellent Introduction, Sparse on Details
Review: While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.