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STAT3032 Survival Models

Later Year Course

Offered By School of Finance, Actuarial Studies & Appl Stats
Academic Career Undergraduate
Course Subject Statistics
Offered in Second Semester, 2010 and Second Semester, 2011
Unit Value 6 units
Course Description

This course introduces survival models and discusses their estimation and their application to mortality. Topics covered will include: an introduction to the life table; survival models; estimation procedures for lifetime distributions; statistical models of transfers between multiple states; maximum likelihood estimation of transition intensities for such models; binomial model of mortality including estimation and comparison with multiple state models; exposed to risk and methods for smoothing crude mortality rate data.

Learning Outcomes

On completion of the course students should understand and be able to apply the techniques outlined in the course description.

 

Indicative Assessment

Assessment for this course will comprise:

  • Mid Semester Exam 20%
  • Final Examination 80%
Workload

10 hours per week

Areas of Interest Actuarial Studies and Statistics
Requisite Statement

STAT2001 Introductory Mathematical Statistics and STAT2008 Regression Modelling

 

Prescribed Texts See Course Website:  http://ecocomm.anu.edu.au/courses/course.asp?code=STAT3032
Preliminary Reading

See Course Website:  http://ecocomm.anu.edu.au/courses/course.asp?code=STAT3032

 

Indicative Reading List See Course Website:  http://ecocomm.anu.edu.au/courses/course.asp?code=STAT3032
Other Information

For further information please refer to http://ecocomm.anu.edu.au/courses/course.asp?code=STAT3032

Academic Contact See http://ecocomm.anu.edu.au/courses/course.asp?code=STAT3032

The information published on the Study at ANU 2010 website applies to the 2010 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2009 website.

Updated:   13 Nov 2015 / Responsible Officer:   The Registrar / Page Contact:   Student Business Solutions