A book not mentioned yet is Marc Kery’s “Introduction to WinBUGs for 
Ecologists.”  Though the focus is on Bayesian stats and WinBUGs, this book has 
2 fabulous features

-straight forward ecological examples of all major statistical procedures in R, 
from t-tests to GLMMs.

-simulated data is used so you can understand the link between the model and 
the theoretical data-generating processes.

The chapter on GLMMS in the follow up book is also excellent and works through 
the process of simulating and analyzing increasingly more complex GLMMs (Kery 
and Schuab “Bayesian population anlysis using WinBugs”)

 

UseR! Has many great titles, though most are of the form “how to do X in R”, 
where “X” includes “basic statistics”, “geo statistics” and “Bayesian 
computation.”  If you are interested specifically in “X” they are awesome, but 
in my experience it’s harder to find general material for the intermediate R 
user.

If you want to improve general programming skills (writing functions and loops, 
using apply) Stevens’ “A Primer of Ecology with R” is excellent, though the 
text focuses on the ecology, not why things were coded a certain way.

 

Paradis’ “Analysis of Phylogenetics and Evolution with R” has a short but good 
appendix introducing some basic programming concepts.

 

Phil Spector’s “Data manipulation with R” is a good introduction (though at 
times dense).  It has chapters on reshaping data and regular expressions; it is 
a bit out of date wrt data manipulation b/c I don’t think it covers the dplyr 
package.  

 

The Bolker book was mentioned in a previous email.  Preprints of some materials 
are on his website

http://ms.mcmaster.ca/~bolker/emdbook/index.html

This is a fabulous book but most appropriate if you are delving into writing 
your own statistical routines and doing your own optimization.

 

 

From: Ecological Society of America: grants, jobs, news 
[mailto:[email protected]] On Behalf Of Stefanie Broszeit
Sent: Wednesday, May 11, 2016 6:25 AM
Subject: Re: Learning R -- summary of replies.

 

Dear Jason et al,

The Use R! Series from Springer is a good collection of books all with the aim 
to explain R in a simple and non-too-jargony way. They are short and not too 
expensive, here is the website (not only ecology, but you can find your way to 
those): http://www.springer.com/series/6991?detailsPage=titles

Good luck!

Stef

 

On Tue, May 10, 2016 at 6:34 PM, Jason Hernandez <[email protected] 
<mailto:[email protected]> > wrote:

Someone requested that I share a summary of replies to my earlier query about 
useful books for learning R, after finishing _R for Dummies_. Here it is: 

 

R. Ben Bolker's "Ecological Models and Data in R" was recommended as a basic 
ecology-oriented one.

 

Bivand's "Applied Spatial Data Analysis with R" is more spatially oriented, as 
is the more recent Brunsdon's "An Introduction to R for Spatial Analysis and 
Mapping".

 

A masters' stats class used "getting started with R, An introduction for 
biologists", by Beckerman and Petchey.

 

Another educator recommended the R for Ecologists website at Montana State 
University: http://ecology.msu.montana.edu/labdsv/R/labs/R_ecology.html. 
Another online resource is the R Inferno. Another is "R for Starters," by Ole 
Forsberg: http://www.rfs.kvasaheim.com/

 

"How to be a Quantitative Ecologist" by Jason Matthiopoulos was another 
recommendation. Also "Community Ecology: Analytical Methods using R and Excel" 
by Mark Gardener. "Biostatistical Design and Analyses Using R" by Murray Logan.

 

At least two users suggested Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. 
A., and Smith, G. M., 2009. "Mixed effects models and extensions in ecology 
with R," especially for mixed effects models including time series, glms, and 
analysis of overdispersed and zero inflated data.

 

Now I just need to decide which one to go with. No way can I afford all the 
books, so it looks like I'll be starting with the online resources.

 

Jason Hernandez

 




-- 

Stefanie Broszeit

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