« Data and Analysis/Applied Data Analysis

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The aim of this course is to equip students with the skills and knowledge to extend their data analysis experience beyond that which is taught in Data Analysis and Interpretation.


  1. Constructing time series datasets
  2. Analysing trends and seasonality
  3. Forecasting and predicting future outcomes

Learning outcomes 

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

  1. Explain the key concepts of time series data analysis
  2. Outline the strengths and weaknesses of existing time series datasets from an analysis perspective
  3. Identify the appropriate analytical technique for time series 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: DATA22

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.

View all Upcoming Micro-credentials