Visual Analytics for Data Scientists using SAS

Subject code: MA5821:03

To be effective an organisation needs to be able to build its data assets by translating raw operational data into strategic information for decisions, data collaborations, personalising services to customers, for making predictions and for forecasting. A data scientist is one of the key contributors to this type of activity and should be able to identify and work with a range of tools and data structures to ensure organisations stay effective and efficient in a competitive world. In this unit, you will be encouraged to learn skills required to succeed in today’s highly analytical and data-driven economy using robust industry tested software for data science. 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 maybe 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.

Software platform: SAS exclusively 


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
  • Critically examine different approaches to advanced statistical problems.

Assessment

Assessment for this course will occur at various times across the seven-week study period. Tasks may include online quizzes, discussion board activity, portfolio development, case studies, reflection, literature reviews presentations and reports.Feedback will be provided to you throughout the study period as well as a final grade at the conclusion of the study period.


This is one of the interdisciplinary subjects studied in the online Master of Data Science

Please note, course structure and content are subject to change. For information on all course subjects download the course guide.

 

Download Course Guide

Ready to get started?

Speak with an Enrolment Advisor

Investing in the right course for you is important to us and we’re here to help. Simply request a call back and will assist you with:

  • Entry requirements
  • Choosing right course
  • How to apply and enrol
  • How online study works
  • Course duration and fees
Enquire Now

Download a course guide

For more detailed and up-to-date information about your degree, including:

  • Information about the course
  • Course duration
  • Fees
  • Course descriptions
  • What to expect from the course
Download course guide