Introduction to SPSS (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.

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

Syllabus

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 month: Bioinformatics Hacky Hour, ask bioinformatics analysis, software and pipeline questions
- Last Tuesday of the month: BioLab Hacky Hour, ask about experimental design and technical sample processing questions to get started in the lab