10 Credits AUTUMN

Aims/Description: Many problems in modern social and physical science, both pure and applied, demand the use of inferential statistical methods for the interrogation of large datasets. Good examples include health policy, education, political issues, economic regeneration, crime and migration, climate and glaciological changes, and the occurrence of natural hazards such as volcanic eruptions. The module is designed to provide students with a solid grounding in the proper application of inferential statistical methods in geographical analysis, and an appreciation of their role in the study of contemporary social and environmental processes. This is achieved through a combination of lectures, practicals and seminars which cover the underlying ideas, provide hands-on experience and give examples of the methods' application in the literature. The module covers hypothesis testing, bivariate inferential methods, and multivariate inferential methods.

Staff Contact: Professor Charles Pattie
Teaching Methods: Lectures, Seminars, Laboratory work, Independent Study
Assessment: Formal Exam, Non-invigiliated practical assignment

Information on the department responsible for this unit (Geography):

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