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EC5216 - Econometrics and Big Data Analysis

Credit points: 3
Year: 2020
Student Contribution Band: Band 3
Administered by: College of Business, Law & Governance

In a day and age in which the availability of big data increases exponentially, the value of the skills to correctly analyse such data increases accordingly. This subject demonstrates a range of econometric models that can be used to interrogate or mine large datasets to test theories and ideas. The subject focuses on the application of these models, understanding their limitations and correctly interpreting their results. The subject provides valuable skills to students in economics, finance or any other discipline in which the analysis of big data is or will be important.

Learning Outcomes

  • formulate testable scientific hypotheses, demonstrating creativity and initiative as a result of a coherent understanding of economic theories;
  • show advanced and integrated knowledge of a range of models to test hypotheses to select an appropriate econometric model;
  • conduct an econometric analysis (including specification tests) using real life big data and critically evaluate the results of econometric models.

Subject Assessment

  • end of semester exam (50%)
  • case study (30%)
  • mid-term exam (20%).
Inadmissible
Subject
Combinations:
BX3122 BX3022

Availabilities

Townsville, Internal, Study Period 1
Census Date 26-Mar-2020
Coord/Lect: Dr Rabiul Beg.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 26 hours lectures
  • 12 hours tutorials
  • 12 hours workshops/Seminars
  • assessment and self-directed study

External, Study Period 1
Census Date 26-Mar-2020
Coord/Lect: Dr Rabiul Beg.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 0 hours
  • assessment and self-directed study
Method of Delivery: WWW - LearnJCU

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.