Availabilities:
| Location | Domestic | International |
|---|---|---|
| Gold Coast | Term3 | Term3 |
| Melbourne | N/A | Term3 |
| Online | Term3 | N/A |
Unit description
Provides students with the necessary knowledge and skills to effectively use business analytics to support decision making in the context of ‘big data’ as a strategic resource. As a ‘data-driven’ unit, students will be exposed to a variety of analytical techniques using software applications.
Unit content
Module 1: Summarising sample data
Module 2: Simple linear regression
Module 3: Multiple linear regression
Module 4: Business Forecasting (Part I)
Module 5: Business Forecasting (Part II)
Module 6: Model Building
Learning outcomes
Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.
| On completion of this unit, students should be able to: | |
|---|---|
| 1 | Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource. |
| 2 | Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage. |
| 3 | Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes. |
| 4 | Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings. |
On completion of this unit, students should be able to:
- Appraise the role of data analytics and implications of big data in helping organisations identify new opportunities and turn big data into a strategic resource.
- Identify patterns and trends for transformation of big data into meaningful information for use to gain competitive advantage.
- Apply statistical techniques using industry software to analyse relationships in the data for forecasting and evaluation purposes.
- Evaluate and communicate results of analysis in a framework for translating data analysis into decision-making outcomes in a variety of business settings.
Prescribed Learning Resources
- Berenson, ML, Levine, DM, Szabat, KA, Watson, J, Jayne, N & O’Brien, M, 2019, Basic Business Statistics: Concepts and Applications, 5th edn, Pearson, Melbourne, VIC. ISBN: 9781488617249.
- No prescribed resources/equipment.
Teaching and assessment
Fee information
Domestic
Commonwealth Supported courses
For information regarding Student Contribution Amounts please visit the Student Contribution Amounts.
Fee paying courses
For postgraduate or undergraduate full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees
International
Please check the international course and fee list to determine the relevant fees.