Course Title: Data Modelling Techniques for Business
Part A: Course Overview
Course Title: Data Modelling Techniques for Business
Credit Points: 12.00
Important Information:
Course Title Amendment
2024 Data Modelling Techniques for Business
2023 Econometric Techniques
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
ECON1223 |
City Campus |
Undergraduate |
625H Economics, Finance and Marketing |
Face-to-Face |
Sem 1 2006, Sem 1 2007, Sem 1 2008, Sem 1 2009, Sem 1 2010, Sem 1 2011, Sem 1 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 1 2016, Sem 1 2017, Sem 1 2018, Sem 1 2019, Sem 1 2020 |
ECON1238 |
City Campus |
Postgraduate |
625H Economics, Finance and Marketing |
Face-to-Face |
Sem 1 2008, Sem 1 2010, Sem 1 2011, Sem 1 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 1 2016, Sem 1 2018, Sem 1 2019, Sem 1 2020 |
Course Coordinator: Dr Pratima Srivastava
Course Coordinator Phone: +61 3 9925 5905
Course Coordinator Email: pratima.srivastava@rmit.edu.au
Course Coordinator Location: 80.11.60
Pre-requisite Courses and Assumed Knowledge and Capabilities
None.
Course Description
Much of the data available to model in economics, finance and related disciplines involves features that make the application of the linear regression model inappropriate. This course will discuss a range of techniques that can be used to deal with such situations. These modelling techniques need to take account of the features of both the data generating and the data collection processes. The course is concerned with both the theoretical issues involved and with the application of the techniques. You will use an econometric software package that enables estimation of the models covered in the course.
Objectives/Learning Outcomes/Capability Development
-
On successful completion of this course you will be able to:
- Undertake empirical analysis using correct analytical techniques.
- Discuss coherently, logically and in a scholarly manner the findings of research activities.
- Reflect on findings of analysis, justifying judgements and decisions.
- Discuss and present findings of research activities in a logical, coherent and succinct manner independently and/or as a member of a group.
- Analyze data in an ethical manner, avoiding selective use of data, concealing of results and fabrication of outcomes.
Overview of Learning Activities
In this course you will be encouraged to be an active learner. Your learning will be supported through various in-class and online activities comprising individual and group work. These may include quizzes; assignments; prescribed readings; sourcing, researching and analysing specific information; solving problems; conducting presentations; producing written work and collaborating with peers on set tasks or projects.
Overview of Learning Resources
Various learning resources are available online through MyRMIT Studies\Canvas. The lecture notes and workshop notes are posted on Canvas.
Resources are also available online through RMIT Library databases and other facilities. Visit the RMIT library website for further details. Assistance is available online via our chat and email services, face to face at our campus libraries or via the telephone on (03) 9925 2020.
Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.
Overview of Assessment
The assessment alignment list below shows the assessment tasks against the learning outcomes they develop.
Assessment Task 1: 50%
Linked CLOs:1, 2, 3, 4, 5
Assessment Task 2: 50%
Linked CLOs: 1, 2, 3
Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on practical exercises and by individual consultation.