Description 

The aims of this micro-credential is to equip enrollees with the skills and confidence to operate in the world of ‘big data.’ The micro-credential will take a social science perspective and to discuss the role of social science and theory in analysing and interpreting ‘big data.’ The micro-credential will not be technical, but rather use key examples of ‘big data’ being used to inform policy to help motivate and engage with the issues. Enrollees will become familiar with some of the technological options and constraints in the storage and analysis of ‘big data’.

Topics 

1. Introduction to data linkage
2. Analysis of linked and transactional data
3. Combining linked and survey data

Learning outcomes 

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

1. Explain the key concepts of data linkage
2. Outline the strengths and weaknesses of existing administrative datasets from an analysis or policy perspective
3. Identify the appropriate analytical technique for analysis of linked or administrative data
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.

Details 

Course Code: DATA23

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.