Digital Economy and Analysis
Your upfront cost: $0
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Our student advisors are here to guide you with:
- Enrolling and eligibility
- Fee and loan information
- Credit and recognition for prior learning
After successfully completing this course you should be able to:
- Describe basic economics principles and techniques with application to the digital economy;
- Analyse the dynamic of the digital economy in relation to the implications, challenges and innovation opportunities it presents;
- Discern appropriate data analytic techniques and apply them to an innovative business context;
- Analyse data for decision making in applied and innovative business context.
ASSURANCE OF LEARNING
This course has been designed to collect data regarding your capacity to identify and critically analyse sources of data to inform evidenced based decision making.
- Basic economic concepts & digital economy
- How markets work in the digital economy?
- Information economics & digital economy
- Digital economy & structural change
- Digital economy, innovation & growth
- Data analysis, big data & digital economy
- Working with data
- Basic probability
- Estimation and testing of hypotheses
- Analysing relation between variables
- Basic forecasting
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
- GRF-AFE133-Economics for Decision Making 1 (No longer available)
- Equipment requirements - Audio/Visual equipment
This course introduces students to the basic economic principles and techniques (both micro and macro) with particular applications to the digital economy. Understanding of these principles and techniques equip students with relevant foundational skills to analyse the dynamic of the digital economy in relation to the implications, opportunities and challenges it presents. With digital economy the world has also seen an exponential increase in the amount of data generated per second. When strategically managed and analysed, data transform into useful information for business decision making. As such, this course further equips students with basic data analytic skills in applied business context.
- Written Assignment (40%)
- Problem Solving Assignment - Computing 1 (30%)
- Problem Solving Assignment - Computing 2 (30%)
For textbook details check your university's handbook, website or learning management system (LMS).