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    <p>I'll mention a few that i think are excellent resources but that i haven't seen mentioned on SO. They are all free and freely available on the Web (links supplied).</p> <p><strong><em><a href="http://www.ats.ucla.edu/stat/dae/" rel="noreferrer">Data Analysis Examples</a></em></strong> A collection of individual examples from the UCLA Statistics Dept. which you can browse by major category (e.g., "Count Models", "Multivariate Analysis", "Power Analysis") then download examples with complete R code under any of these rubrics (e.g., under "Count Models" are "Poisson Regression", "Negative Binomial Regression", and so on). </p> <p><strong><em><a href="http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf" rel="noreferrer">Verzani: SimpleR: Using R for Introductory Statistics</a></em></strong> A little over 100 pages, and just outstanding. It's easy to follow but very dense. It is a few years old, still i've only found one deprecated function in this text. This is a resource for a brand new R user; it also happens to be an excellent statistics refresher. This text probably contains 20+ examples (with R code and explanation) directed to fundamental statistics (e.g., hypothesis testing, linear regression, simple simulation, and descriptive statistics).</p> <p><strong><em><a href="http://zoonek2.free.fr/UNIX/48_R/all.html" rel="noreferrer">Statistics with R</a></em></strong> (Vincent Zoonekynd) You can read it online or print it as a pdf. Printed it's well over 1000 pages. The author obviously got a lot of the information by reading the source code for the various functions he discusses--a lot of the information here, i haven't found in any other source. This resource contains large sections on Graphics, Basic Statistics, Regression, Time Series--all w/ small examples (R code + explanation). The final three sections contain the most exemplary code--very thorough application sections on Finance (which seems to be the author's professional field), Genetics, and Image Analysis. </p>
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