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You may want to buy personal copies of some of the books below. The Mathematics Library has reserve copies for you (students on this course) to use there, except the Berry and Lindgren book (I have a copy you can use here, on request).
There are no required texts for this course, however, it is strongly recommended that you purchase a reference book for each of R/S-Plus and LaTeX Which book is up to you. Some suggestions are:

• Modern Applied Statistics with S-Plus by William Venables and Brian Ripley, published by Springer-Verlag. Highly recommended for this and other courses, and for future use as a reference text.
  
  
• An Introduction to R (approx. 100 pages, 650kB), based on the former "Notes on R", gives an introduction to the language and how to use R for doing statistical analysis and graphics.
  
  
• LATEX: A Document Preparation System -- User's Guide and Reference Manual by Leslie Lamport, published by Addison-Wesley. 2nd Edition. This is my favorite, but many other LaTeX guides are equally good and are essentially exchangeable. For example,
• The LaTeX Companion by M Goossens, F Mittelbach and A Samarin, published by Addison-Wesley. I use this one too
• A Guide to LaTeX -- Document Preparation for Beginners and Advanced Users by H. Kopka and P. Daly, published by Addison-Wesley. Another popular guide to LaTeX.
• Math into LaTeX -- An Introduction to LaTeX and AMS-LaTeX by George Gratzer, published by Birkhauser. Still yet another LaTeX book.
  
  
• Additional resources:
  • The S-Plus manuals. Duke Statistics has several copies of the S-Plus manuals which provide useful discussion of lots of statistical models and methods as well as computing details.
  • As useful as (if not more than) manuals is the on-line help system: in S-Plus simply type

     	help.start()  
    
    to fire this up, then search by keywords. This on-line help system is 
    excellent and indispensible. 
    
    In R just type 
    
                help() 
    
              

  • Check the computing link for other links to support material on unix, editors, S-Plus, etc.

There are many introductory statistics texts that cover essentially the same range of basic probability theory and statistical models and methods. A couple of really good ones you might consult from time to time are noted below. In addition, a lot of relevant material at an introductory level is available in some of the notes -- much won't be explictly covered, but you should find lots of the material there useful and it is easy to browse.

• Probability and Statistics by Morris H DeGroot, published by Addison Wesley (2nd Edn). An excellent traditional (but now older text) on basic theory and methods.This covers basic elements of both Bayesian and non-Bayesian approaches to statistics and has been a standard introductory text for many years. Many other texts cover similar material on the non-Bayesian side
  
  
• Statistics: Theory and Methods by Don Berry and Bernard Lindgren, published by Duxbury. An excellent standard introductory text, written by one Bayesian and one non-Bayesian statistician.

More specifically on Bayesian ideas and methods:

• Bayesian Data Analysis by Andrew Gelman, John B Carlin, Hal S Stern and Don B Rubin, published by Chapman & Hall. It is a more advanced statistical modelling text that goes beyond the scope of this course, but it is a truly excellent text for both statistical modelling and applications, is full of good reading on concepts, and has many examples. It is used in several follow-on statistics courses in Duke Statistics.
  
  
• Bayesian Approach to Interpreting Archaeological Data by Caitlin Buck, William Cavanagh and Cliff Litton, published by Wiley. Archaeology? Sounds curious, but this is an excellent statistics book. Chapters 3-7 provide an excellent introduction to basics of probablity and statistical modelling from a Bayesian perspective. The book has lots of applied material, mostly from archaeology, that is worth reading.