20 Credits ACADEMIC YEAR


Pre-requisites: MAS223


Aims/Description: The unit develops concepts and techniques for the analysis of data having the complex structure typical of many real applications. The two main themes are the analysis of observations on high-dimensional data, and the analysis of dependent observations made over a period of time on a single variable. Machine learning lies at the interface between computer science and statistics, whose aims are to develop a set of tools for modelling and understanding complex data sets. A review of repeated measures problems links to ideas of time series analysis. General techniques for the study of time series are developed, including structural descriptions, Box-Jenkins and state-space models and their fitting, techniques for forecasting and an introduction to spectral methods

Staff Contact: JARVIS ASHLEY F
Teaching Methods: Lectures, Independent Study
Assessment: Formal Exam, Project/ portfolio

Information on the department responsible for this unit (Mathematics and Statistics):

Departmental Home Page
Teaching timetable

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NOTE
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

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Teaching methods and assessment displayed on this page are indicative for 2021-22. Students will be informed by the academic department of any changes made necessary by the ongoing pandemic.

Western Bank, Sheffield, S10 2TN, UK