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Central Queensland University (CQU)

31 May, 2016

9:00 am - 3:00 pm

Instructors: Paula Andrea Martinez, Jason Bell

Helpers: Amanda Rebar

General Information

Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design 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: This course is being run as a one-day, standalone R session. Interested people (RHD candidates/early career researchers/researchers/staff) who want to learn R are welcome to attend. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: CQUniversity North Campus, Building 10 Library, Room G.18-2, Rockhampton North, Queensland. Get directions with OpenStreetMap or Google Maps.

Requirements: You will need to bring a laptop with the specific software packages installed as detailed below. We will also use the UCQ High Performance Computing account, if you do not have one already please get in touch. Remember you are required to abide by Software Carpentry's Code of Conduct.

Contact: Please mail j.bell@cqu.edu.au for more information.


Schedule

Surveys

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

Pre-workshop Survey

Post-workshop Survey

Day 1

08:30 Setting up and software installation help
09:00 Introduction to R and R studio
10:30 Morning tea
11:00 R for data manipulation
12:30 Lunch break
13:30 Graphing and using packages in R
15:00 Wrap-up

Etherpad: http://pad.software-carpentry.org/cqu-r.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.


Syllabus

R for data analyis

  • Introduction to R and R studio
  • Working with vectors and data frames
  • Reading and plotting data
  • Using R from the command line
  • Reference...

Setup

Wireless Internet Access

You will be able to access wireless internet through eduroam - please check your institution's IT support pages for how to connect. Try to connect to eduroam at your institution before you come to the workshop as this saves a lot of time.

R

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

Windows

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

Mac OS X

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

Linux

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 yum install R). Also, please install the RStudio IDE.