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Resources for Statistics

This is a list of resources that I have personally used or found useful.  I own and have read all the books (not always cover to cover), used the software, etc. and these are my favorites or the ones I think do the best job at whatever they are trying to do (at least of what I have tried).  Sorely missing from my book list currently is a basic introductory statistics text and one on regression.  I have read 4 - 5 introductory texts, and I am less than thrilled with each for various reasons.  I have thoroughly gone through one regression book; it did a decent job, but I am not really excited about it.

General

UCLA Statistical Consulting
This website has numerous guides and examples from a variety of statistical software suites.

Los Angeles RUG R user group
Los Angeles GPGPU meetup group that is on parallel computing

Software

This list is not meant to be exhaustive, it represents what I have used and my top recommendations.  In addition to software for data analysis (statistics, graphics, etc.), if you start doing much with statistics, it becomes very convenient to have a good text editor for working with code/syntax.  This facilitates writing, commenting, viewing, saving, taking notes on, etc. code.  Depending which one you choose, it may also work on many platforms.  My favorite by far is Emacs paired with ESS.  This provides syntax highlighting among many other features.  It is also nice because it works on Linux, Mac OS, and Windows, which simplifies life when switching operating systems. 

R Project the main R website
R Search an easy way to search the R helplist archives (and documentation)
Crantastic a website with ratings, reviews, and some usage levels for R packages

OpenMX structural equation modeling software that works with R

ggplot2 probably my favorite R package for graphics

GNU Emacs (powerful text editor)
ESS short for Emacs Speaks Statistics, this is an extremely useful add-on if you use Emacs.

Books

Statistics

• Robert Rosenthal & Ralph L. Rosnow. Essentials of Behavioral Research: Methods and Data Analysis (3rd ed.). McGraw-Hill, New York, 2008. ISBN 978-0-07-353196-0
  
  
• Robert Rosenthal. Meta-Analytic Procedures for Social Research (2nd ed.). Sage Publication, Newbury Park, CA, 1991. ISBN 9780803942462
  
  
• Edward R. Tufte. The Visual Display of Quantitative Information (2nd ed.). Graphics Press, 2001. ISBN 978-0961392147
  
  
• William S. Cleveland. The Elements of Graphing Data (Second ed.). Hobart Press, 1994. ISBN 978-0963488411
  
  
• Books on Data Visualization a wealth of readings on graphing and visualizing data I put together over on the ggplot2 wiki
  
  
• Judith D. Singer & John B. Willet. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press, 2003. ISBN 978-0-19-515296-8
  
• Andrew Gelman & Jennifer Hill. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press, 2006. ISBN 978-0521686891

More computationally oriented

• R Books a list of books for R from the R project website
  
  
• Peter Dalgaard. Introductory Statistics with R (2nd ed.). Springer, 2008. ISBN 978-0-387-79053-4
  
  
• Hadley Wickham. ggplot: Elegant Graphics for Data Analysis. Use R. Springer, 2009. ISBN: 978-0-98140-6
  
  
• William N. Venables & Brian D. Ripley. Modern Applied Statistics with S (4th ed.). Springer, New York, 2002. ISBN 0-387-95457-0
  
  
• Jose C. Pinheiro & Douglas M. Bates. Mixed-Effects Models in S and S-Plus. Springer, 2000. ISBN 0-387-98957-0
  
  
• William N. Venables & Brian D. Ripley. S Programming. Springer, New York, 2000. ISBN 0-387-98966-8
  
  
• John M. Chambers. Software for Data Analysis: Programming with R. Springer, New York, 2008. ISBN 978-0-387-75935-7

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