Resources

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• Web site for the required text by Fox, J. (1997). Applied Regression Analysis, Linear Models, and Related Methods.
• Free version of the regression book by J. J. Faraway (2002) Practical Regression and Anova using R.
• R language:
  • The Comprehensive R Archive Network (CRAN) The home for R. Includes software and documentation. 
  • An Introduction to R from the CRAN web site.
  • An Introduction to R A four-hour version of the intro by Cori Mar, CSDE, University of Washington.
  • R regression functions handout by Vito Ricci.
  • A reference text: Venables, W. N. and Ripley, B. D. (1997) Modern Applied Statistics with S-Plus, 2nd edition, Springer.
• Computing resources on campus:
  • Math Sciences Computing Center Lab located in Communications Building.
  • The Center for Social Science Computation and Research (CSSCR) located in Condon Hall (rooms 611, 609, 601a-g).
• Data bases:
  • Inter-University Consortium for Political and Social Research
  • CSSCR Data Archive
  • University of Michigan Statistical Resources (Beware dead links on this site)
  • StatLib, Carnegie Mellon University.
  • Statistical Science Web data sets.
  • Statistical datasets, University of Massachusetts, Amherst.
• Resources on mathematical/statistical concepts:
  • Math review from the Math Camp by the Center for Statistics and the Social Sciences, University of Washington.
  • Mathworld, an extensive mathematics resource.
  • Rice virtual lab in statistics, containing an online statistics book, simulations, demonstrations and case studies.
• Resources on writing:
  • Alley, M(1996) The Craft of Scientific Writing, 3rd edition, Springer.
  • Higham, N. J. (1993) Handbook of Writing for the Mathematical Sciences, Siam.
  • Ehrenberg, A.S.C. (1981).  The problem of numeracy.  The American Statistician 35:67-71.
  • Ehrenberg, A.S.C. (1982). Writing technical papers or reports. The American Statistician 36:326-329.
  • Freeman, D.H., Jr., Gonzalez, M.E., Hoaglin, D.C. and Kilss, B.A. (1983). Presenting statistical papers. The American Statistician 37:106-110.
  • A nice list of mostly common sense guidelines: http://writing.caltech.edu/resources/tech-writing-tips.html