Below are a few books that would be helpful in supplementing other material used in the course:
[CLRS] Introduction to Algorithms
by Thomas H. Cormen, Chales E. Leiserson, Ronald R. Rivest, and Clifford Stein, MIT
Press, 2009 (3rd edition). Standard textbook for algorithms' courses.
[NRC] Numerical Recipes in C: The Art of Scientific Computing
by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery, Cambridge University Press. One of the more comprehensive references for computational algorithms and tricks. Chapters from the older version (2nd edition) can be downloaded for free.
by Stephen Boyd and Lieven Vandenberghe, Cambridge University Press, 2004. The book can be downloaded for free from the author's website.
[NW06] Numerical Optimization
by Jorge Nocedal and Stephen J. Wright, 2nd edition, Springer, 2006. The is available as an eBook (for free from Purdue) from Springer.
In general, take a look at Use R! book series published by Springer. Purdue appears to have electronic access (in PDF) to chapters of these books. There are a few books in this series which can provide a sufficient background in R for this course.
A Beginner's Guide to R
by Alain F. Zuur, Elena N. Ieno, Erik H.W.G. Meesters, Springer, 2009. A very basic introduction to R. PDF
chapters of this book is available online if accessed from Purdue computers.
Introductory Statistics with R
by Peter Dalgaard, 2nd edition, Springer, 2008. “Practical methods” in statistics heavily illustrated with the help of R.