Description 

The aim of this micro-credential is to equip students with the skills and knowledge to analyse existing data to create new social science and policy insights.

Topics 

1. The concept and practice of statistical hypothesis tests
2. Descriptive statistics and distributional analysis
3. Introducing multivariate analysis – linear regression
4. Extending multivariate analysis – non-linear regression
5. The power and practice of longitudinal data analysis

Learning outcomes 

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

1. Explain the key concepts of data analysis
2. Outline the strengths and weaknesses of existing datasets from an analysis perspective
3. Outline a hypothesis test and explain the use of null and alternative hypotheses, as well as one and two-sided tests
4. Identify the appropriate analytical technique for different types of variables
5. Discuss some of the main assumptions underlying different techniques
6. 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 

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 is undertaken as a stand-alone course.

Details 

Course Code: DATA05

Workload: 21 hours 

• Contact hours: 8 hours
• Individual study and assessment: 13 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Maria Jahromi

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