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MA5821 - Visual Analytics for Data Scientists using SAS

Credit points: 3
Year: 2022
Student Contribution Band: Band 1
Administered by: College of Science and Engineering

This subject will introduce students to practical applications and concepts involved in advanced statistical modelling in SAS. Topics include: linear modelling with multiple predictor variables that may be continuous or categorical in nature; Conditional Probability and the odds ratio; drawing inferences; checking model diagnostics and model selection; techniques for coping with data that are temporally or spatially correlated.

Learning Outcomes

  • demonstrate sound knowledge of the basic principles and theories that underpin advanced statistical modelling methods;
  • effectively integrate and execute advanced statistical modelling theories and processes in SAS software to solve authentic problems;
  • retrieve, analyse, synthesise and evaluate outputs produced using advanced statistical modelling methods in SAS software;
  • engage effectively with others to critically examine different approaches to advanced statistical problems.

Subject Assessment

  • Written > Literature review - (40%) - Individual
  • Written > Workbook - (60%) - Individual.


JCU Online, Study Period 83, External
Census Date 19-May-2022
Workload expectations:

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

  • 65 hours - Online resources including readings, screencasts, embedded quizzing.
  • assessment and self-directed study
Method of Delivery: Online - JCU
Restrictions: Enrolment in this offering is restricted.

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.