Statistics short courses

Keep abreast of the latest developments in statistical analysis by enrolling in one of our short courses or single units of study.

Choose a short course program (non-assessable), designed to expand and update your skills, or a single unit of study (assessable) which may be credited to your degree.

Our short courses are ideal for researchers in any area, especially health, market, business or social research, or current research students who need to add to their qualifications or stay up to date with the latest techniques and technology.

Our teaching emphasises practical application, so what you study will be of immediate use in your current work.

Courses and single units of study

Many of our degree units run once a week over a semester. Research students and others are welcome to enrol in a single unit or selected topics. If you choose to be assessed, you may be able to credit the unit to other degree study.

Swinburne higher degree by research (HDR) students and supervisors wanting statistics training or help, please see Statistics Training (login required). These courses are free for Swinburne HDR students and staff.

If you're external to Swinburne and would like statistics training, please use the Statistics Short Course Application Form.

Weekly evening short courses

  • Basic Statistics
  • Simple Linear Regression and ANOVA
  • Introduction to R
  • Using R for Statistical Analysis     
  • Introduction to SAS
  • Survey Design
  • Research Design
  • Multiple Linear Regression
  • Factor Analysis and MANOVA
  • Advanced Topics in Regression: Generalised Linear Model
  • Advanced  Topics in Regression: Mixed Models, Multi-level Models and Survival Analysis
  • The Basics of Scale Development
  • Rasch Modelling
  • Introduction to SPSS
  • Further SPSS

Course enquiries

Dr Prahan Apputhurai
Department of Health Science and Biostatistics
Phone: +61 3 9214 3703

Custom training and consulting

If you don't see what you are looking for, contact us to express your interest in learning about a particular topic. For example, we can provide instruction in SAS, R, Bayesian statistics, scale development, logistic regression, loglinear modelling, survival analysis, cluster analysis, conjoint analysis, correspondence analysis and multidimensional scaling.

We also invite you to enquire about tailored in-house courses and one-on-one consultations.

Associate Professor Stephen Quinn
Department of Health Science and Biostatistics
Phone: +61 3 9214 8412