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James Cook University Subject Handbook - 2023

For subject information from 2025 and onwards, please visit the new JCU Course and Subject Handbook website.

EC5216 - Econometrics and Big Data Analysis

Credit points:03
Year:2023
Student Contribution Band:Band 4
Administered by:College of Business, Law & Governance

Subject Description

    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

  • Written > Examination (centrally administered) - (50%) - Individual
  • Written > Test/Quiz 1 - (20%) - Individual
  • Written > Research report - (30%) - Individual

Note that 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.

Inadmissible Subject Combinations:  BX3122 BX3022

Availabilities

Townsville Bebegu Yumba, Trimester 3, External

Census date:Thursday, 05 Oct 2023
Study Period Dates:Monday, 11 Sep 2023 to Saturday, 09 Dec 2023
Coordinator(s):
DR Rabiul Beg
Lecturer(s):
DR Rabiul Beg
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 30 Hours - Online activity - Recordings, online activities & self-directed learning
  • 10 Hours - Online Tutorials - Online collaborate sessions
Method of delivery:WWW - LearnJCU