| Offered By: |
School of Finance and Applied Statistics |
| Academic Career: |
Graduate Coursework |
| Course Subject: |
Statistics |
| Offered in: |
Second Semester, 2010 |
| Unit Value: |
6 units |
| Course Description: |
This course is intended to introduce students to generalised linear modelling methods for both discrete and continuous response data. Review of multiple linear regression and the analysis of variance; use of transformations and weighting in linear models. Logistic regression for binary response data. Generalised linear models; estimation and inference using iteratively re-weighted least squares (IRLS). Poisson regression; loglinear models for contingency tables. |
| Learning Outcomes: |
Introduction to generalised linear modelling methods, structural assumptions and diagnostics for both discrete and continuous responses. |
| Indicative Assessment: |
- Mid semester exam (1 hour) 20%
- Final exam (3 hours) 80%
|
| Workload: |
10 hours per week |
| Course Classification(s): |
|
| Areas of Interest: |
Actuarial Studies and Statistics |
| Eligibility: |
At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with at least two years of university level statistical and mathematical study including calculus and linear algebra, as well as mathematical statistics and linear regression theory. |
| Incompatibility: |
with STAT8030 Generalised Linear Modelling |
| Prescribed Texts: |
See Course Website: http://ecocomm.anu.edu.au/courses/course.asp?code=STAT7030 |
| Preliminary Reading: |
See Course Website: http://ecocomm.anu.edu.au/courses/course.asp?code=STAT7030 |
| Indicative Reading List: |
See Course Website: http://ecocomm.anu.edu.au/courses/course.asp?code=STAT7030 |
| Programs: |
Graduate Certificate in Actuarial Studies and Master of Applied Statistics |
| Other Information: |
For further information please refer to http://ecocomm.anu.edu.au/courses/course.asp?code=STAT7030 |
| Academic Contact: |
See http://ecocomm.anu.edu.au/courses/course.asp?code=STAT7030 |