I like: Applied Linear Statistical Models by Neter, Kutner, Nachtsheim, and Wasserman (McGraw Hill)
It is not specific to any stats package, but it gives a good mix of theory behind the routines and how to apply them and covers a good breadth of material. A must have for statistics and R is: Modern Applied Statistics with S by Venables and Ripley (Springer). This gives specific examples and commands to use in S-plus/R along with more background information and theory than the R tutorials. Once you have the theory down, a couple more books that help with the practical aspects of using R to do the analysis are: A Handbook of Statistical Analyses Using R by Everitt and Hothorn (Chapman & Hall/CRC) An R and S-PLUS Companion to Applied Regression by Fox (Sage) There may be other good ones out there that I am not familiar enough with to recommend. Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.s...@imail.org 801.408.8111 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r- > project.org] On Behalf Of Monte Milanuk > Sent: Friday, January 23, 2009 9:57 AM > To: r-help@r-project.org > Subject: [R] Stat textbook recommendations? > > Hello, > > I'm looking for a textbook that can explain some of the math behind > the intro-to-intermediate stuff like ANOVA, multiple regression, non- > parametric tests, etc. > > A little background: I took an intro stats course last year and > would like to further my education. Being as that was the highest > (and only) stats class the local community college offers, it looks > like I'm on my own from here. I've been working through some of the > online 'stats with R' tutorials as well as Dalgaard's ISWR. Where > I'm running into problems is the transition from Bluman's 'A Brief > Introduction to Elementary Statistics' (covers up through paired t- > tests, chi-squared/goodness-of-fit, simple linear regression & > correlation, and just barely mentions ANOVA) with a TI-83+, to even > books like ISWR... when they start getting into the things like one > and two-way ANOVA, multiple regression, model selection, survival, > etc. I start feeling like I have one hand tied behind my back - I > just don't have enough theoretical exposure to really understand what > techniques I would use when, relative to my own projects outside the > book. > > Several of the 'intro to stats using R' books and pdf tutorials > mention that they are not really meant as a standalone statistics > text book, but in addition to a traditional stats textbook (Verzani > mentions Kitchen's book specifically). So I guess what I'm looking > for is any other recommendations on intro or intermediate textbooks > that deal primarily with the math/theory behind the processes. If > they were oriented towards R that's be great, but otherwise I guess > I'd be most interested in something relatively platform-agnostic - > I've seen some books that were slanted heavily towards a particular > software package (Minitab) that I cannot afford or justify for > personal use. > > TIA, > > Monte > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.