Principles of statistical inference (6 points)
(MED)
Leader: Dr I Marchner
Offered:
Clayton Second semester 2004 (OCL)
Clayton Second semester 2005 (OCL)
Synopsis:
Objectives: On completion of this unit the student will: 1. have a deeper understanding of fundamental concepts in statistical inference and their practical interpration and importance in biostatistical contexts; 2. understand the theoretical basis for frequentists and Bayesian approaches to statistical inference; 3. be able to develop and apply paremetric methods of inference, with particular reference to problems of relevance in biostatistical contexts; 4. have the theoretical basis to understand the justification for more complex statistical procedures introduced in subsequent units; 5. have an understanding of basic alternatives to standard likelihood-based methods, and be able to identify situations in which these methods are useful.
Assessment: Two written assignments + Practical exercises
Prerequisites: EPM5002
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