This is a QCIF 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.

This practical workshop will help participants to choose and use the appropriate statistical test for their data by introducing key concepts of inferential statistics in R. Participants will learn how to compute, report, and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA.

Pre-workshop preparation

Attendees must have previous experience in R and the RStudio interface. PCs are available but ideally they should bring a laptop with wireless internet access, configured for the Eduroam network and with R and RStudio pre-installed

While you are waiting, get started with R and RStudio:

NOTE: The examples used in this course will be from bioinformatics. You may also want to consider attending the R sessions in the Library. See the Library's training link for more information on the latest sessions.

About Research software and programming

At UQ, there are many research tools available at your disposal. Preview the available research software and programming languages and learn the pros and cons of each. Investigate how to use them to effectively analyse, manipulate, and visualise your research data.
 

Library workshops

The library offers a range of workshops under the headings below including:

R with RStudio  Excel for research data  NVivo Pro

Useful links

  • Library's software training resources
  • Software carpentry: The open-source movement to teach basic lab skills for research computing.
  • REDCap consortium: A secure web application for building and managing online surveys and databases. UQ is a member of the consortium
  • RStudio cheat sheets
  • Hacky Hour (supported by RCC, QCIF, IMB and wonderful volunteer helpers!): RCC runs consultations every Tuesday at Cafe Nano. Come and ask IT questions such as: getting started with Python and R, stats, machine learning, bio-image, software tools, research data management (RDM), how to access high performance computing, cloud data storage and tools for data cleaning and data visualisation. Bring your project's IT problems or come along as a helper! Very occasionally Hacky Hour may not run; follow us on Twitter (@HackyHourStLuc​) to get the latest announcements. Aside from the usual IT research questions, 
    • First Tuesday of the monthBioinformatics Hacky Hour, ask bioinformatics analysis, software and pipeline questions
    • Last Tuesday of the monthBioLab Hacky Hour, ask about experimental design and technical sample processing questions to get started in the lab