Advanced Modelling and Analytics
Duration
- One Semester or equivalent
Contact hours
- 72
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
| Hawthorn HOL Study Period 3 |
||
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
Con-current Pre-Requisite
Equivalent
Aims and objectives
This unit of study expands on earlier units in the course, introducing students to other aspects of statistical modelling and analytics. In particular, students will be introduced to models that allow for a variety of non-normal distributions and complex data structures.
Unit Learning Outcomes (ULO)
Students who successfully complete this unit will be able to:
1. Appraise the structure and nature of data to select an appropriate analysis technique
2. Contrast a variety of advanced linear regression techniques allowing for various response distributions and managing missing data appropriately
3. Apply various multi-level methods for the analysis of nominal and metric response variables.
4. Evaluate and identify risk factors that contribute to survival outcomes
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
On-campus Tutorial | 1 | 12 | 12 |
Online Learning activities | 3 | 12 | 36 |
Unspecified Activities Independent learning | 8.5 | 12 | 102 |
TOTAL | 150 hours |
Hawthorn Online
Type | Hours per week | Number of Weeks | Total |
Live Online Class | 1 | 12 | 12 |
Online Directed Online Learning and Independent Learning | 11.5 | 12 | 138 |
TOTAL | 150 hours |
Assessment
Types | Individual/Group Role | Weighting | Unit Learning Outcomes (ULOs) |
Assignment | Individual | 50% | 1, 2, 3, 4 |
| Online Quizzes (10) | Individual | 10% | 1, 2, 3, 4 |
| Final-Semester Test | Individual | 40% | 1, 2, 3, 4 |
Content
- Analysis of categorical response data: binary, ordinal, multinomial, loglinear models
- Generalized linear models (GLM)
- Survival analysis
- Multi-level modelling
- Generalized estimating equation (GEE)
- Mixed models
- Managing missing data
Study resources
- Reading materials.
Reading materials
Students are advised to check the unit outline in the relevant teaching period for appropriate textbooks and further reading.