
I conceded to R shift (mostly) last year and began Crawley (2005) Statistics: An Introduction using R.  Quinn and Keough: Experimental Design and Data Analysis for Biologists is very useful, but if given a choice of the two with the emphasis on learning R, Crawley might be preferable.  Better yet might even be the "R Book".

-Brian

> Date: Mon, 10 Nov 2008 12:30:22 -0800
> From: cparker@pdx.edu
> To: r-sig-ecology@r-project.org
> Subject: Re: [R-sig-eco] classical statistics in R
> 
> I agree with Jordan and will also throw in Gelman and Hill's "Data 
> Analysis Using Regression and Multilevel/Hierarchical Models". Its a 
> social science based book but is very relevant to ecologists and 
> includes R code (and bugs code).
> -Chris
> 
> 
> Jordan Mayor wrote:
> > Personally, I found G&E to be very helpful at only a cursory interest level.
> >  Quinn & Keough's "Experimental Design and Data Analysis for Biologists" is
> > a practical in-depth text that covers allot more detail - but, alas no
> > R-code is provided.  In fact, it is quite program-independent.
> > 
> > Cheers
> > 
> > On Mon, Nov 10, 2008 at 3:10 PM, tyler <tyler.smith@mail.mcgill.ca> wrote:
> > 
> > 
> >>Hi,
> >>
> >>I've just received my copy of Ben Bolker's new book, "Ecological Models
> >>and Data in R". I was a little surprised to see he recommended Sokal and
> >>Rohlf's "Biometry" as an introduction to classical stats. Not because
> >>there's anything wrong with S&R, it's comprehensive and well-written.
> >>My problem with this book is that it's written from the perspective of
> >>filling out tables of sums of squares according to fixed recipes, while
> >>R is geared towards more flexible linear models. Trying to translate the
> >>more complex recipes into R code is not a trivial task.
> >>
> >>In response to an email, Ben suggested that Gotelli and Ellison's
> >>"Primer of Ecological Statistics" provides a more modern take on the
> >>subject than S&R. I have to agree, G&E is one of the best intros I've
> >>seen for ecologists. But it doesn't really go very far into the possible
> >>complexities of ANOVA and linear regression, and doesn't specifically
> >>address implementing tests in R.
> >>
> >>Ben and I are both curious as to what other r-sig-eco readers think
> >>about this issue. What are the best sources for learning about classical
> >>statistics as implemented in R? S&R has been the standard reference for
> >>quite a while, but it now appears to be dated. Is there a good standard
> >>text that covers the same breadth of material with a modern, R-compatible
> >>approach? Ben also recommended several books by Michael Crawley - any
> >>strong feelings on these, or other suggestions?
> >>
> >>Thanks!
> >>
> >>Tyler
> >>
> >>--
> >>Research is what I'm doing when I don't know what I'm doing.
> >>                                      --Wernher von Braun
> >>
> >>_______________________________________________
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> >>R-sig-ecology@r-project.org
> >>https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
> >>
> > 
> > 
> > 
> >
> 
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