Principles of Statistical Inference

This subject has the following teaching availabilities in 2008:

505-105 Mathematics Background for Biostatistics

505-975 Probability and Distribution Theory

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

Review of the key concepts of estimation, and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests; methods of inference based on likelihood theory, including use of Fisher and observed information and likelihood ratio; Wald and score tests; an introduction to the Bayesian approach to inference; an introduction to distribution-free statistical methods.

Objectives: To provide a strong mathematical and conceptual foundation in the methods of statistical inference, with an emphasis on practical aspects of the interpretation and communication of statistically based conclusions in health research.

Two written assignments to be submitted during semester worth 35% each (approx 10 hrs work each).

Submission of selected practical exercises throughout the semester worth 10% each (approx 6 hrs work each).

Printed course notes and assignment material by mail, email, and online interaction facilities.

Special Computer Requirements: SAS or Stata Statistical Software

Azzalini, A. Statistical Inference: Based on the Likelihood. Chapman and Hall, London, 1996

Clayton and Hills. Statistical Models in Epidemiology. Oxford University Press, Oxford, 1993.

This subject is not available as a breadth subject.

Independent problem solving, facility with abstract reasoning, clarity of written expression, sound communication of technical concepts.

Level: 400

This subject is not available in the Master of Public Health.

Subject Coordinator: Ms Adrienne Kirby, University of Sydney (adrienne@ctc.usyd.edu.au; 02 9562 5064)