Data Carpentry at UM: Data Analysis and Visualization with R

University of Mississippi

September 9, 2024

9:00 am - 4:30 pm

Instructors: Savannah Kelly, Harley Rogers

Helpers: Shelby Watson, Abbie Norris Davidson, Mahek Sota, Kenaz Worthem, Achala Gaihre

General Information

The Carpentries project comprises the Software Carpentry, Data Carpentry, and Library Carpentry communities of Instructors, Trainers, Maintainers, helpers, and supporters who share a mission to teach foundational computational and data science skills to researchers.

Want to learn more and stay engaged with The Carpentries? Carpentries Clippings is The Carpentries' biweekly newsletter, where we share community news, community job postings, and more. Sign up to receive future editions and read our full archive: https://carpentries.org/newsletter/

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Jackson Avenue Center, Room A. Get directions with OpenStreetMap or Google Maps.

When: September 9, 2024; 9:00 am - 4:30 pm Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

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

We are dedicated to providing a positive and accessible learning environment for all. We do not require participants to provide documentation of disabilities or disclose any unnecessary personal information. However, we do want to help create an inclusive, accessible experience for all participants. We encourage you to share any information that would be helpful to make your Carpentries experience accessible.

Glosario is a multilingual glossary for computing and data science terms. The glossary helps learners attend workshops and use our lessons to make sense of computational and programming jargon written in English by offering it in their native language. Translating data science terms also provides a teaching tool for Carpentries Instructors to reduce barriers for their learners.

Contact: Please email carpentries@olemiss.edu or slkelly@olemiss.edu for more information.

Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.


Code of Conduct

Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.


Collaborative Notes

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


Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


Schedule

Day 1

Before starting Pre-workshop survey
9:00 am Introduction to R
10:30 am Break
12:00 pm Lunch
1:00 pm Continuation of R: Data Analysis & Visualization
2:30 pm Break
4:15 pm Post-workshop survey
4:30 pm END

Setup

To participate in a Data Carpentry workshop, you will need access to software as 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

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

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

Instructions for R installation on various Linux platforms (debian, fedora, redhat, and ubuntu) can be found at <https://cran.r-project.org/bin/linux/>. These will instruct you to use your package manager (e.g. for Fedora run sudo dnf install R and for Debian/Ubuntu, add a ppa repository and then run sudo apt-get install r-base). Also, please install the RStudio IDE.