Davis R Users' Group
“The sweetest Rhelp group this side of the Mississippi.”
Welcome to the Davis R Users’ Group (DRUG)! We are a community of R users at UC Davis who support each other in using R for science. Our focus is providing a space for beginning and intermediate users to learn from each other.
Come to our weekly work sessions: This is the core purpose of DRUG. We have weekly, 2hour work sessions where people bring their computers to work on their own projects, and ask each other questions as needed. We have no TAs  just mutual support in R, statistics, and related topics. Group members sometimes give short presentations on R methods and best practices or to get feedback on their projects.
For Fall Quarter 2015, weekly work sessions will be be held Wednesdays 10AM12PM in Wickson Hall Room 2120J
Join the mailing list: The mailing list is an online supplement to our inperson work sessions.
Use the resources below: We’ve compiled a list of resources to help you get started using R and find answers to your questions.
We’re fortunate to have sponsorship from Revolution Analytics for our snacks and speaker prizes.
Resources for R Help
Getting Started  DRUG Resources Web Resources  Mailing Lists  Books  Courses  Misc  Stats at UCD
Please Add Additional Resources in the Comments! I will add them to the page.
Some tips on getting started:
 Download R here
 After you install R, I recommend you install RStudio. RStudio is a program that makes R easier to use, and is being widely adopted by both beginning and advanced R users. Importantly, it works across most computer platforms, and has features that make it easy to share your work, collaborate, and do proper version control.
 Google is your first stop for most questions. You’ll most likely reach most of the resources below while searching for your specific question.
 Our regular R work sessions and listserv are great places to ask questions, especially if you are not sure what you are looking for.
DRUG tutorials from our meetings
Sometimes DRUG members put together useful resources and tutorials for our meetings which we post on the blog under the “DRUG” tag:
 Qualitative Text Analysis in R with RQDA
 First Steps with Structural Equation Modeling
 Visualizing fits, inference, implications of (G)LMMs with Jaime Ashander
 Back to basics: High quality plots using base R graphics
 Back to basics: High quality plots using base R graphics
 An introduction to ggplot with Myfanwy Johnston
 Making Maps in R with Ryan Peek and Michele Tobias
 Carl Boettiger on accessing online data with ROpenSci
 Tim Bowles on multivariate stats with vegan
 Ongoing learning with user groups
 Michael Levy on Data Manipulation using dplyr
 Vectorization in R: Why?
 Using Dates and Times in R
 Ryan Peek on Creating Shiny Apps
 How to format plots for publication using ggplot2 (with some help from Inkscape)
 Dave Harris on Maximum Likelihood Estimation
 Robert Hijmans on Spatial Data Analysis
 FasteR! HigheR! StrongeR!  A Guide to Speeding Up R Code for Busy People
 Debugging Tools in R with Michael Hannon

Demographic analysis using the
popbio
library and some other fun stuff  Model Selection and MultiModel Inference
 Mason Earles on interfacing R with the Forest Vegetation Simulator
 Ryan Peek on using xts and ggplot for timeseries data

Steve Culman on the
plyr
Package  Don’t R alone! A guide to tools for collaboration with R
 Exploring GAMs with Rosemary Hartman
 Ryan Peek on Customizing Your R Setup
 Chris Hamm on using plot.new() for better combined plots
 Stella Copeland’s Intro to Mixed Models in R
 A quick introduction to ggplot()
Web Resources
Everyone learns R differently, for different purposes. Thus, you’ll probably need to learn specialized packages for your field or application. Resources and books here are generalpurpose, with some bent towards ecological statistics applications.
There’s no need to reinvent the wheel. Here are lists of beginner’s resources which others have compiled. R tools evolve rapidly, though, so be sure to check that your guide is uptodate!
 Rseek is a search engine for R resources.
RStudio’s Getting Help with R page or online learning page.
 Beginner tips from Revolution Analytics
 A free online course from Coursera
For more advanced usage, Hadley Wickham’s Advanced R is a free ebook and he is also writing a book on creating R packages
Online materials from an Rbased ecological statistics course from UNC.
Books
 R in a nutshell by Joseph Adler is a good book that’s available in the Davis library and online for Davis users.
 Ecological Models and Data with R by Ben Bolker.
 The Art of R Programming
 Introductory R
 A Primer of Ecology with R by M. Henry H. Stevens is also available online
Other Mailing Lists, Discussion Boards and Resources
These mailing list are very useful not just as a place to ask questions. They are probably where you will find your answers when you search on Google.
 The RHelp mailing list and it’s many subgroups, including an Ecologyspecific group
 Stack Overflow is a popular Q&A site for computer programming that a lot of discussions about R.
 The Davis Scientific and Statistical Computing List is mostly used by advanced users and includes some of the developers of R.
R Courses at Davis
There are a few courses at UC Davis that use R.
 Duncan Temple Lang (one of the developers of R) teaches Statistical Computing (STA141), a course mostly about R but also more general topics in computer science for statistics. He also organizes an informal seminar series on statistical computing. STA 242 is a more advanced version of the course. He also will teach STA 135  Multivariate Data Analysis this year, which is not about R but uses R for data exploration, data mining, and regression.
 Richard McElreath’s Statistical Rethinking (ANT298) is a course in Bayesian statistical methods which doesn’t focus on R but teaches enough for the applications in the course.
 Marissa Baskett and Sebastian Schreiber teach Computational methods in population biology (ECL298) in alternate years. This course also isn’t explicitly about R but teaches enough basics so as to be able to use it for the applications in the course. They also created this handy cheat sheet
 Design, Analysis, and Interpretation of Experiments (PLS 205) has in the past provided an optional extra section to learn techniques in R in addition to SAS
 Carole Hom teaches Introduction to Dynamic Models in Modern Biology (BIS 132) where R is used for differential and difference equation modeling.
 There are occasional paid workshops offered on campus
 At least one section of STA100 uses R
 Robert Hijmans teaches Quantitative Geography (GEO200CN). It is a survey course about spatial data analysis and modeling using R, including subjects such as point pattern analysis, kriging, inference, cellular automata and Markov chains. It has lectures, disussions, and a intensive lab.
 Jim Fadel teaches ABG250: Mathematical Modeling in Biological Systems, which uses R and teaches enough for the applications in class
 Anna Steel taught ECL298: R for Dummies: Basics of data manipulation in R Winter Quarter 2013. The course may be taught by someone else in the future, but is still up in the air.
 The political science methods sequence (POL211, POL212, POL213) uses R.
 Andrew Latimer’s Applied Statistical Modeling for Environmental Science (PLS298) uses R in addition to JAGS and OPENBugs. It assumes familiarity with R.
Miscellaneous
 Rbloggers
 The One R Tip A Day Twitter Account
 #rstats is a common hashtag for discussing R on Twitter
General Statistics Resources at UC Davis
 Here is a page compiling stats and modeling courses that Ecology students can take at UC Davis
 The UC Davis Department of Statistics has a consulting service that is free for disserationrelated statistical advice. You get a 1hour meeting with a statistician to discuss your research and they will send you a writeup of their recommendations.