Online Event

22 April 2020

9:00 am - 5:00 pm

Instructors: Rebecca Lange, Kathryn Napier

Helpers: Rebecca Lange, Kathryn Napier, Cara Kreck, Nancy Tippaya

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: This is an online workshop. Dial in details will be provided to Registrants one week prior to the workshop.

When: 22 April 2020. 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).

Contact: Please email curtinic@curtin.edu.au for more information.


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.


Surveys

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

Pre-workshop Survey

Post-workshop Survey


Schedule

Day 1

08:30 Join online workshop and set up
09:00 Introduction to the workshop and tools
09:45 Coffee break
10:00 Introduction to R
11:00 Coffee break
11:15 Introduction to R continued / Manipulating, analyzing and exporting data with tidyverse
12:15 Lunch break (provide your own at home!)
13:00 Manipulating, analyzing and exporting data with tidyverse continued
14:00 Coffee break
14:15 Data visualization with ggplot2
15:15 Coffee break
15:30 Data visualization with ggplot2 continued
16:30 Wrap-up

Syllabus

Data Analysis and Visualisation in R

  • Finding your way around RStudio and getting help
  • Project set up
  • Manipulating, analyzing and exporting data with tidyverse
  • Data visualisation with ggplot2
  • Reference...

Setup

To participate in a Software Carpentry 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

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.

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.