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]]
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.snow at imail.org 801.408.8111> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of Monte Milanuk > Sent: Friday, January 23, 2009 9:57 AM > To: r-help at 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 at 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.
You might want to check out the following: http://www.stochas.org/ http://www1.appstate.edu/~arnholta/PASWR/index.htm http://turtle.gis.umn.edu/pmwiki/pmwiki.php/StatisticsandDatawithR/HomePage http://www.janehorgan.com/ I own all of these books and like them. The book by Dr. Jan Horgan: "Probability with R: An Introduction with Computer Science Applications" is nice in that it's quick and right to the point. Don't let the title fool you, there's plenty of information applicable to all fields. The book by Dr. Kenneth Baclawski: "Introduction to Probability with R" is has more theory than the previous book and also has lots of worked problems. The other two books are general prob/stat books, I find they're both extremely well written with the Arnholt book with a little more theory. All of these books start from first principles (no required stat background, just some math) but I suspect that all of these may be a good next step to bridge the gaps that you mention. In addition, I think that owners of PASWR and SADWR may be able to get a solution manual from the author (if you're working on your own and not taking a class). Cheers, Dan Viar Chesapeake, VA On Fri, Jan 23, 2009 at 11:57 AM, Monte Milanuk <memilanuk at gmail.com> wrote:> > 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 at 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.
If you don't want to be on your own, and you are looking for more statistics courses than you have available locally, Texas A&M University statistics department offers some single courses, a 4-course certificate, and an entire masters degree, all online, no campus visits required. I am in their masters program now. Colorado State University offers similar things, also no campus visits needed. --Chris Christopher W. Ryan, MD SUNY Upstate Medical University Clinical Campus at Binghamton 40 Arch Street, Johnson City, NY 13790 cryanatbinghamtondotedu PGP public keys available at http://home.stny.rr.com/ryancw/ "If you want to build a ship, don't drum up the men to gather wood, divide the work and give orders. Instead, teach them to yearn for the vast and endless sea." [Antoine de St. Exupery] Monte Milanuk wrote:> 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. . . .
(resending to include r-help) Monte Milanuk wrote:> 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.Re. ISwR, you might want to take notice that it was originally written for a course that used Altman's "Practical Statistics for Medical Research". It is, however, a bit wordy for some and glosses rather too quickly over the math. Another popular item for ambitious beginners is Kirkwood and Sterne: Essential Medical Statistics. Their notation is a bit maddening (for teachers anyway) but they do cover a lot of ground without digging too deeply into the math. If you want more math, beware that what is good, strongly depends on your prerequisites. Linear model theory, e.g., gets much easier with matrix calculus and nearly trivial if you know about abstract linear algebra and projections in N dimensional vector spaces. For relatively basic levels, look at booke that are popular for first courses in Engineering: Devore, Johnson+Miller+Freund, and probably more. -- O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
Monte, Here is an entire book released to public domain from earlier publication by Elsevier http://pubs.usgs.gov/twri/twri4a3/ William On Jan 23, 2009, at 10:57 AM, Monte Milanuk wrote:> 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 at 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.