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
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