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, 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.
Please help us select a time for the upcoming quarter.
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.