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MA2405 - Advanced Statistical Modelling

Credit points: 3
Year: 2019
Student Contribution Band: Band 2
Administered by: College of Science and Engineering

This course includes lectures and practicals on statistical methods in the applied sciences. Topics include exploratory data analysis, estimation of linear models, inference techniques (including bootstrapping and permutation testing), prediction, model diagnostics, model selection.

Learning Outcomes

  • demonstrate sound knowledge of the basic principles that underpin regression and analysis of variance models;
  • effectively integrate and execute statistical theories and processes in RStudio;
  • retrieve, analyse, synthesise and evaluate outputs produced from RStudio;
  • integrate statistical principles, methods, techniques and tools covered in this course to plan and execute a statistical analysis;
  • evaluate, synthesise and communicate findings from statistical investigations in a report format.
Prerequisites: MA1401 OR BZ2001 OR MA2401 OR SC2202 OR SC2209


Townsville, Study Period 2, Internal
Census Date 29-Aug-2019
Lecturer: Dr Carla Ewels.
Workload expectations:

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

  • 26 hours lectures
  • 26 hours tutorials
  • assessment and self-directed study
Assessment: end of semester exam (50%); other exams (15%); assignments (35%).

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.