With explosions in availability of computing power and facilities for gathering data in recent times, a key skill of any graduate is the ability to work with increasingly complex datasets. There may include, for example, data sets with multiple levels of observations gathered from diverse sources using a variety of methods. Being able to apply computational skills to implement appropriate software, as well as bringing to bear statistical expertise in the design of the accompanying algorithms are both vital when facing the challenge of analysing complicated data. This unit is made up of three distinct modules, each focusing on a different aspect of applications of statistical methods to complex data. These include (but are not restricted to) the development of a data product that interrogate large and complicated data structures; using sophisticated statistical methods to improve computational efficiency for large data sets or computationally intensive statistical methods; and the analysis of categorical ordinal data. Across all modules you will develop expertise in areas of statistical methodology, statistical analysis as well as computational statistics. Additional modules may be delivered, depending on the areas of expertise of available staff and distinguished visitors.
3 x 1hr lecture/week, 1 x 1hr lab/week
presentations (33%), project 1 (33%), project 2 (14%), quizzes (20%)
This unit is only available in even 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.