Stream C – Analysing Complex Datasets (Advanced)

MFSAS Stream C advanced modules teach statistical techniques for analysing complex datasets and research questions. These are two day workshops that will take participants through hands-on exercises using statistical software (computers supplied).

These workshops are designed for individuals who are proficient in more basic data analysis techniques.


 

Module C1 – Building Statistical Models   (2 days)

 

  • Measurement matters
  • Identifying relationships
  • Building statistical models

 Module overview

 

Next Workshop: 16-17 May, 2017 (9:00am - 5:00pm daily)
Cost: $1100 (student discount 25%)

 


 

Module C2 – Multilevel Models for Clustered and Longitudinal Data   (2 days)

 

  • Analysing grouped or clustered data
  • Variance components for multiple levels
  • Building statistical models with contextual effects

​ Module overview

 

Next Workshops: 5-6 September, 2017 (9:00am - 5:00pm daily)
Cost: $1100 (student discount 25%)

 


 

Module C3 – Longitudinal Data Analysis: Introduction and Panel Regression Methods   (2 days)

 

  • Structuring longitudinal data sets
  • Modelling relationships over time
  • Choosing the right approach to analysis

​ Module overview

 

Next Workshops: 18-19 July, 2017 (9:00am - 5:00pm daily)
Cost: $1100 (student discount 25%)

 


 

Module C5 – Longitudinal Data Analysis: Analysing Complex Datasets    (5 days)

 

  • Managing longitudinal datasets and preparing these for statistical analysis
  • Recognising hierarchical data and the relevance of multilevel models
  • Determining the most appropriate modelling approach for different types of research questions

​ Module overview

 Course brochure

 

Next Workshop: 20-24 November, 2017 (9:00am - 5:00pm daily)
Cost: $3,465 (early bird rate till 25 September) and $4,180 thereafter (student discount 25%)
 

 

Can't attend these dates?

No problem, just join our mailing list at mfsas@uq.edu.au. Tell us which module/s you're interested in and we'll let you know the next time it's being delivered.