The great power of the discipline of Statistics is the possibility to make inferences concerning a large population based on only observing a relatively small sample from it. Of course, this "magic" does not come without a price, we must construct statistical models to approximate these populations and samples from them, develop mathematical tools using probability theory, appreciate the limitations of our methods and, most importantly, understand what assumptions need to be made for such inferences to be valid, and develop ways to check these assumptions. Implementing these methods to possibly complex data structures is also a challenge that must be overcome. This unit explores advanced topics in statistical methodology examining both theoretical foundations and details of implementation to applications. The unit is made up of 3 distinct modules. These include (but are not restricted to) Advanced Survival Analysis, Extreme Value Theory and Statistical Methods in Bioinformatics.
3 x 1hr lecture/week, 1 x 1hr tutorial/week
3 x submitted homework (15%), 2 x assignments (14%), project presentation (20%), 3 x quizzes (51%)
This unit is only available in odd years.
Familiarity with probability theory at 4000 level (e.g., STAT4211 or STAT4214 or equivalent) and with statistical modelling (e.g., STAT4027 or equivalent). Please consult with the coordinator for further information.