« Data and Analysis/Applied Data Analysis

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The aims of this micro-credential is to equip enrollees with the skills and knowledge to extend their survey data analysis experience beyond that which is taught in Data Analysis and Interpretation.


  1. Interaction terms and non-linear models for continuous variables
  2. Analysing non-linear dependent variables
  3. Analysing multi-level datasets
  4. Cluster and factor analysis

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Explain the key concepts of survey data analysis
  2. Outline the strengths and weaknesses of existing datasets from an analysis perspective
  3. Identify the appropriate analytical technique for complex data analysis
  4. Discuss some of the main assumptions underlying different techniques
  5. Design or critique an analysis plan

Indicative assessment 

Assignment 1 – Introductions and identification of data analysis questions (500 words, 20% of final mark) LO: 1, 2

Assignment 2 – Analysis plan (1,500 words, 80% of final mark) LO: 3, 4, 5, 6

Assumed knowledge 

Completion of ANU Micro-credential Data Analysis and Interpretation (or equivalent).

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as part of a stack by completing Data Analysis and Interpretation.


Course Code: DATA24

Workload: 21 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 14 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Professor Nicholas Biddle

This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

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