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.
Help us pick a meeting time for next quarter!
- Come to our weekly work sessions: This is the core purpose of DRUG. We have weekly, 2-hour 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 Spring Quarter 2014, work sessions will be held at 3PM on Mondays in Wickson 2124.
Join the mailing list: The mailing list is an online supplement to our in-person 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 have sponsorship from Revolution Analytics for our snacks and speaker prizes.
Resources for R Help
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.
D-RUG tutorials from our meetings
Sometimes D-RUG members put together useful resources and tutorials for our meetings which we post on the blog under the “D-RUG” tag:
- 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
popbiolibrary and some other fun stuff
- Model Selection and Multi-Model Inference
- Mason Earles on interfacing R with the Forest Vegetation Simulator
- Ryan Peek on using xts and ggplot for time-series data
Steve Culman on the
- 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()
There’s no need to reinvent the wheel. Here are lists of beginner’s resources which others have compiled
- Rseek is a search engine for R resources.
- RStudio’s Getting Help with R Page
- List of Free Online R Tutorials
- Beginner tips from Revolution Analytics
- A free online course from Coursera
- R in a nutshell by Joseph Adler is a good book that’s available in the Davis library and online for Davis users.
- A Primer of Ecology with R by M. Henry H. Stevens is also available online
Other Mailing Lists
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 R-Help mailing list and it’s many subgroups, including an Ecology-specific 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.
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.
- 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 disseration-related statistical advice. You get a 1-hour meeting with a statistician to discuss your research and they will send you a write-up of their recommendations.