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.
R for Reproducible Scientific Analysis - University of New Mexico Health Sciences Center
May 15-19, 2023
1:30 pm - 4:30 pm MDT
Instructors: Jon Wheeler, Todd Quinn, Harry Snow, Lori Sloane
Helpers: Tamara Wheeler, Jose Carlos Cabrerea Zuniga, Matt Manicke
General Information
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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 "Best 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: 900 Camino de Salud NE Albuquerque, NM 87131-001 UNM Bldg#227, Zoom URL:https://hsc-unm.zoom.us/j/95600170294. Get directions with OpenStreetMap or Google Maps.
When: May 15-19, 2023. 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. For workshops at a physical location, the workshop organizers have checked that:
- The room is wheelchair / scooter accessible.
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 lsloane@salud.unm.edu or hsnow@salud.unm.edu for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
Who can attend?: This workshop is open to UNM Health Science Center Researchers.
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.
Schedule
May 15
| Before starting | Pre-workshop survey |
| 13:30 | Setup & Introduction to R, RStudio and RMarkdown |
| 14:30 | Project Management With RStudio |
| 15:00 | Break |
| 15:15 | Seeking Help |
| 15:30 | Data Structures |
May 16
| 13:30 | Exploring Data Frames |
| 14:30 | Splitting and Combining Data Frames |
| 15:00 | Break |
| 15:15 | Data Frame Manipulation with dplyr |
May 17
| 13:30 | Creating Publication-Quality Graphics with ggplot2 | |
| 14:30 | Writing data | |
| 15:00 | Break | |
| 16:15 | (first 3 days of materials) | Post-workshop survey |
May 18
| 13:30 | Introduction to binary response variables |
| 15:00 | Break |
| 15:15 | Introduction to logistic regression |
May 19
| 13:30 | Logistic regression with one continuous explanatory variable |
| 14:30 | Making predictions from a logistic regression model |
| 15:00 | Break |
| 15:15 | Assessing logistic regression fit and assumptions |
| End |
Setup
To participate in a Software 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 .pkg file from CRAN. Also, please install the RStudio IDE.
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.
Acknowledgment
This workshop is funded through the National Science Foundation EPSCoR Cooperative Agreement OIA-1757207. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
