R for reproducible scientific analysis (QCIF) [Webinar]

This is a QCIF/QFAB course and places are highly limited as Graduate School is paying the fee. If you are unable to attend, please de-register (or email graduateschool@uq.edu.au if you are unable to do so). An unexplained absence could result in all your future QCIF registrations becoming Waitlisted. You may only attend the workshop once. Repeat bookings will be removed and placed on the Waitlist.

The emphasis of this workshop is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis.

RECOMMENDED PARTICIPANTS

Researchers looking for more advanced or automated data analysis capabilities than basic spreadsheets. The workshop is relevant for all disciplines. While it is designed to be suitable for people with no previous experience with R or other programming languages, participants do need to be confident and experienced with using computers, and a familiarity with command-line interfaces will be helpful.

LEARNING OBJECTIVES

• Upload and process data in R to generate plots, figures and tables
• Create and run functions in R
• Write your own R script for automated data processing
• Create automated reproducible reports in R
• Install and load external R packages and manage R projects

SYLLABUS

The workshop will use the training material at swcarpentry.github.io/r-novice-gapminder/. Topics covered will include:

• The Rstudio integrated development environment
• The format of the R language - variables, data structures and functions.
• The import, export and processing of data within R
• Generating high-quality graphic presentations of data
• Building dynamic reports for reproducible research

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. Please do not sign up for this workshop if you are unwilling or unable to attend all four mornings. If you are unsure if R is the correct tool for you, you might want to attend the Library's R workshops first.

Pre-workshop preparation:

Attendees will need to have R and RStudio installed – see setup instructions. Alternatively they can set up an account at https://rstudio.cloud. Finally, please download the training datafile to your laptop before the workshop.