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BX3022 - Econometrics

Credit points: 3
Year: 2012
Student Contribution Band: Band 3
Administered by: School of Business

BX3022 provides an elementary but comprehensive introduction to econometrics. The subject is designed to provide a conceptual basis of data analysis. Topics include Classical linear regression, basic regression assumptions, homoskedasticity, heteroskedasticity, serial correlation, multicolinearity, simultaneity, dummy variable, structural break, and nonstationarity. Strong emphasis will be given to application of regression analysis with real data to meet the demands of students from a wide range of business subjects including economics, finance, marketing, accounting, and tourism. Applications are conducted by extensive use of Shazam and/or E-views computer software packages. These are window based software and reasonably easy to use.

Learning Outcomes

  • have an increased understanding of the assumptions underlying regression;
  • demonstrate an ability to use a statistical package to run various different regression models;
  • demonstrate an ability to interpret the regression output of a statistical software package;
  • develop a range of different regression models for business and policy analysis;
  • test the statistical properties of various regression models, correcting for common econometric 'problems', such as multicolinearity, heterskedasticity and auto correlation.

Graduate Qualities

  • The ability to define and to solve problems in at least one discipline area;
  • The ability to deploy critically evaluated information to practical ends;
  • The ability to evaluate that information;
  • The ability to select and organise information and to communicate it accurately, cogently, coherently, creatively and ethically;
  • The ability to reflect on and evaluate learning, and to learn independently in a self directed manner;
  • The ability to manage future career and personal development;
  • The ability to generate, calculate, interpret and communicate numerical information in ways appropriate to a given discipline or discourse;
  • The ability to lead, manage and contribute effectively to teams;
  • The ability to work individually and independently;
  • The ability to select and use appropriate tools and technologies;
  • The ability to use online technologies effectively and ethically.
Prerequisites: BU1007 OR BU1010 OR EC1101 OR MA1401 OR MA2401
EC2413 AND EC3413 AND EC5212 AND EC5412


Townsville, Study Period 2, Internal
Census Date 23-Aug-2012
Coord/Lect: Dr Rabiul Beg.
Workload expectations:
  • 24 hours lectures - face to face lecture
  • 12 hours tutorials - solutions of tutorial exercises
  • 4 hours workshops/Seminars - demonstration and problem solving
Assessment: end of semester exam (% - 30%); other exams (% - 30%); tutorial attendance and participation (% - 10%); assignments (% - 30%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.