The first numerical programming text for any practicioner's shelf. It covers scores of areas, contains scads of code, and is chock full of useful practical advice, delivered in a friendly tone.

An overview of the field by an early practioner. The algorithms profiled aren't the latest and greatest, but the mode of approach to numerical problems outlined here shouldn't be missed.

A fun, helpful, and graphic introduction to mathematical statistics. No, this book won't let you turn off your brain and ignore the math. But it will ease you in to thinking like a statistician.

The classic reference on special functions. You won't find any code here, but you will find nearly every known mathematical property of your favorite function from grad school.

A standard reference on matrix decompositions and eigenvalue problems.

A classic, in-depth treatment by one of the pioneers in the field. Don't use this as an introduction, but when you are ready for the big league, this is a good book to have handy.

A careful exposition of still state-of-the-art algorithms for root-finding in one dimension, and extrema-finding in one and multiple dimensions. Contains (ALGOL) code and rigorous algorithmic analysis.