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MSc Statistical Ecology

  • DeadlineStudy Details:

    1 year

Course Description

 

The PGDip/MSc in Statistical Ecology is a one-year taught programme run by the School of Mathematics and Statistics.

 

This course aims to give you a sound understanding of the statistical foundations of modern methods in statistical ecology, the skills to use these methods effectively, and experience of applying them to real-world problems, under the supervision of experts, some of whom are leading researchers in this field.

 

Highlights

 

 

    • Introduces key concepts and methods in statistical ecology and provides an overview of the field.

 

    • Taught by staff at the Centre for Research into Ecological and Environmental Modelling (CREEM), who have more than two decades’ experience developing, using and teaching methods in statistical ecology.

 

    • Core modules in Semester 1 provide a solid statistical foundation for specialist modules later in the course.

 

    • Optional placements with collaborators in the UK and abroad as part of a supervised summer research dissertation; connects theoretical training with real field studies and professionals.

 

    • Flexible dissertation format, which can include producing a podcast, web page, poster, field report, training materials,a short film.

 

 

Teaching format

 

The course consists of two semesters of taught courses followed by a dissertation undertaken over the summer months.

 

Modules and course material are taught through:

 

 

    • lectures

 

    • one-to-one discussion

 

    • seminars

 

    • small group discussion tutorials

 

 

You may be assessed on your knowledge and understanding of the course through:

 

 

    • examinations

 

    • coursework

 

    • class tests

 

    • presentations

 

    • research essays

 

    • research project.

 

 

Further particulars regarding curriculum development.

 

Entry Requirements

A 2.1 undergraduate Honours degree in a relevant discipline (for example, biological sciences, ecology, mathematics, statistics, environmental sciencecomputer science)a 2.2 in a relevant discipline and equivalent work experience (for example, at least 12 months working in a relevant field).

Fees

For fees and funding options, please visit website to find out more

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