MA5821 - Advanced Statistical Methods for Data Scientists

Credit points:	03
Year:	2019
Student Contribution Band:	Band 2
Administered by:

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.

Prerequisites:

MA5820 AND 12CP OF POSTGRADUATE SUBJECTS

Availabilities
, Study Period 81
Census Date 24-Jan-2019
Contact hours:	65 hours - Online resources including readings, screencasts, embedded quizzing.
Method of Delivery:	Online - JCU
Assessment:	quizzes or tests (20%); assignments (60%); computational laboratories/log book (20%).
, Study Period 85
Census Date 12-Sep-2019
Contact hours:	65 hours - Online resources including readings, screencasts, embedded quizzing.
Method of Delivery:	Online - JCU
Assessment:	quizzes or tests (20%); assignments (60%); computational laboratories/log book (20%).

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.