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 if you are unable to do so). An unexplained absence could result in all your future QCIF registrations becoming Waitlisted.

Recommended Participants

Researchers looking to start using SPSS for basic data analysis and reporting. The workshop is relevant for all disciplines, although examples and exercises will be based around clinical datasets. 

Learning Objectives

  • Import data from other sources into SPSS 
  • Manage data within SPSS, including cleaning and transforming data
  • Generate plots, figures and tables summaries of the data using the SPSS GUI
  • Carry out simple inferential statistical tests


  • Introduction to SPSS
  • Importing Data into SPSS 
  • Data Management and Cleaning 
  • Derived Variables and Transformations 
  • Descriptive Statistics and Data Presentation 
  • Basic Introduction to Statistics Tests 

Pre-workshop preparation

Attendees must have SPSS licence installed on their laptops. Check out the ITS self-service to download SPSS.

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