Practical Data Analysis

Recommend course:


This eight session course picks up where Using Data leaves off to enable you to do your own analysis. It will also help you better understand the analysis done by others so it can inform your own work or so you can play the increasingly important role of data translator within your organisation.

Who should attend:

This course is intended for people who:

  • need or want to use data as part of their job, and 
  • have done the Using Data course (or have equivalent knowledge), but 
  • have not had formal statistical training (or have forgotten what they learned if they did).

Learning objectives:

  • Understand what analytical techniques are appropriate in a given situation based on the objective and available data. 
  • Learn to use statistical software.
  • Be able to execute various forms of data analysis independently. 
  • Deepen awareness of some of the issues to consider when working with data.

Course outline:

Session 1:

  • Introduction
  • Coding qualitative data

Session 2:

  • Introduction to statistical software
  • Differences in means and proportions

Session 3:

  • Correlations
  • Regression analysis

Session 4:

  • Logistic regression

Session 5:

  • Discriminant analysis

Session 6:

  • Factor analysis

Session 7:

  • Cluster analysis

Session 8:

  • Data hygiene
  • Experimental design
  • Wrap-up

Course format:

This is an eight half-day session course with gaps between the sessions to enable participants to apply what they have learned in the previous session before attending the next session. Each session will involve a combination of lecture, group discussion, and hands-on activities.


Mary Ellen Gordon

Further details:
If you would like more information about this programme, please contact us on: 
Ph: 64 4 463 6556 Email:

Customised workshops: 
Victoria Professional and Executive Development are able to customise many of our workshops to meet specific individual or organisational requirements. Please contact us for further information.

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