Application deadline

Thursday 10 August 2023

Applicants should apply as early as possible to be eligible for certain scholarships and for international visa purposes.

“The best part of studying here is the location of St Andrews; the beaches, historical monuments and great walks everywhere. It is a very demanding course and especially requires you to do a lot of maths – help is available but you must be willing to work for it.”

Jeevan
- Khotang, Nepal

Entry requirements

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

You should also have undergraduate training in mathematics and statistics at SCQF Level 8, or equivalent experience.

If you studied your first degree outside the UK, see the international entry requirements.

You must be able to demonstrate English language proficiency. See English language tests and qualifications.

The qualifications listed are indicative minimum requirements for entry. Some academic Schools will ask applicants to achieve significantly higher marks than the minimum. Obtaining the listed entry requirements will not guarantee you a place, as the University considers all aspects of every application including, where applicable, the writing sample, personal statement, and supporting documents.

Application requirements

CV
personal statement (optional)
two original signed academic references
academic transcripts and degree certificates .

For more guidance, see supporting documents and references for postgraduate taught programmes.

English language proficiency

If English is not your first language, you may need to provide an English language test score to evidence your English language ability. See approved English language tests and scores for this course.

Course details

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, applying 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, or a short film.

Modules

The modules published below are examples of what has been taught in previous academic years and may be subject to change before you start your programme. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the module catalogue.

The modules in this programme have varying methods of delivery and assessment. For more details about each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue, which is for the 2022-2023 academic year; some elements may be subject to change for 2023 entry.

Students typically take the following modules. However, students with adequate statistical training or experience may be exempt from one or both of the first two modules listed below and may take other optional modules instead. 

Computing in Statistics: teaches computer programming skills, including principles of good programming practice, with an emphasis on statistical computing.
Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalised linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.
Modelling Wildlife Population Dynamics: introduces students to methods for constructing mathematical models of wildlife population dynamics and of fitting these models to diverse data from wildlife surveys.
Estimating Animal Abundance and Biodiversity: introduces the main types of survey methods for wildlife populations.

As part of their optional choices, all students must take:

Any statistics-focused module at level 5000 in the School (those with module codes beginning MT57 in the module catalogue, or ID5059).
One additional module at level 3000, 4000, or 5000 in the School (those with module codes beginning with MT3, MT4 or MT5 in the module catalogue).

Students who have been exempted from taking one or both of 'Introductory Data Analysis’ or 'Applied Statistical Modelling Using GLMs' may instead choose other relevant modules in statistics.

All students are recommended to include one of the following two modules in their choices:

Advanced Data Analysis
Multivariate Analysis

Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University's position on curriculum development).

During the final three months of the course, MSc students complete a dissertation or a portfolio dissertation to be submitted by the end of August. Dissertations are supervised by members of teaching staff who will advise on the choice of subject and provide guidance throughout the progress of the dissertation.

A number of options for placements with organisations within the UK are available to work on a range of real-world problems specified by the organisations. Placements may range from a few visits to the organisation, to being hosted by the organisation for a large part of the dissertation. Students on placements will be co-supervised by scientists at the organisation and St Andrews staff. International placements will also be available, with similar supervision arrangements. International placements involve an additional cost.

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PGDip instead of an MSc.

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.

Events

There are a number of different seminars held each week in the School of Mathematics and Statistics. These include:

Statistics

Pure Mathematics

Applied Mathematics

Applied Mathematics seminars

Fees

Home
£11,120

Overseas
£23,530

More information on tuition fees can be found on the postgraduate fees and funding page.

Funding and scholarships

The University of St Andrews is committed to attracting the very best students, regardless of financial circumstances.

Taught postgraduate scholarships Postgraduate loans

After your degree

Careers

Statistical skills are highly valued in ecology and conservation, with modern ecological methods becoming increasingly quantitative. The course is therefore excellent preparation for a career as a scientist in:

government environment agencies
industry
consultancies
wildlife, conservation, and environmental organisations.

Graduates may also work as wildlife managers, using their analytical skills to better inform management decisions.

The Careers Centre offers one-to-one advice to all students as well as a programme of events to assist students in building their employability skills.

Further study

The MSc in Statistical Ecology prepares students for further postgraduate studies in quantitative ecology, conservation, or statistics applied to ecological problems.

The MSc is taught by members of the world-leading Centre for Research into Ecological and Environmental Modelling (CREEM), and graduates may continue their education by enrolling for a PhD within CREEM or within statistics, biology, wildlife, ecology, or conservation departments worldwide. 

Postgraduate research

What to do next

Online information events

Join us for one of our information events where you can find out about different levels of study and specific courses we run. There are also sessions available for parents and college counsellors.

Postgraduate online visiting days

We encourage all students who are thinking of applying to the University to attend one of our online visiting days.

Contact us

Phone: +44 (0)1334 46 2344
Email: maths-pgstats@st-andrews.ac.uk
Address: School of Mathematics and Statistics
Mathematical Institute
North Haugh
St Andrews
KY16 9SS

School of Mathematics and Statistics website

Statistical Ecology (PGDip/MSc) 2023 entry