R for Reproducible Scientific Analysis

Aug 28-29, 2019

9:00 am - 4:30 pm

Instructors: Sue McClatchy, Dan Gatti

Helpers: Michael Wilczek, Angie Reed

General Information

Where: Barrows Hall Room 126, University of Maine, Orono, ME. Get directions with OpenStreetMap or Google Maps.

When: Aug 28-29, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.). They should have a few specific software packages installed (listed below). They are also required to abide by the Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email susan.mcclatchy@jax.org for more information.


Wednesday, Aug 28

09:00 Workshop Overview
09:30 Introduction to R and RStudio
10:25 Project Management With RStudio
10:45 Coffee
11:00 Seeking Help
11:20 Vectors
12:30 Lunch break
13:30 Vectorization
13:45 Control Flow
14:45 Coffee
15:00 Functions Explained
16:25 Wrap-up
16:30 End

Thursday, Aug 29

09:00 Creating Publication-Quality Graphics with ggplot2
10:45 Coffee
11:00 Dataframe Manipulation with dplyr
12:00 Exploratory Data Analysis
12:30 Lunch break
13:30 Exploratory Data Analysis (continued)
14:00 Tibbles
14:30 Data Import
14:45 Coffee
15:00 Tidy Data
15:30 R Markdown
16:00 R Markdown Formats
16:25 Wrap-up
16:30 End

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


Programming in R


To participate in a workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.


R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.


Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.


Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.


You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.