Statistical Ecology (PGDip/MSc) 2024 entry

Learn the modern statistical methods currently used by professionals in ecology, including how to formulate problems, conduct appropriate analyses and effectively communicate results to a variety of audiences. To balance theory and application, placement opportunities will be available with partner organisations within the UK and abroad.

Start date
September 2024
End date
June 2025 (PGDip) or September 2025 (MSc)
Ten months full-time (PGDip) or one-year full-time (MSc)
School of Mathematics and Statistics

Application deadline

Thursday 8 August 2024

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.”
- Khotang, Nepal

Entry requirements

  • A good 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. 


    • 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. 


    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.

    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.  

    • 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. 
    • Software for Data Analysis: covers the practical computing aspects of statistical data analysis.
    • 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 also have the option to apply to enrol in the following modules offered by the School of Biology: 

    • Population Biology  
    • Advanced Bioacoustics for MarineMammal Science

    Please note that both Biology modules are only available subject to a cap on numbers with Biology students having priority. 

    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. 


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


    Pure Mathematics 

    Applied Mathematics 




    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.

    15% Recent Graduate Discount

    If you have graduated from the University within the last three academic years, you may be eligible for a 15% discount on postgraduate taught tuition fees. Terms and conditions apply.

    Taught postgraduate scholarships    Postgraduate loans

    After your degree


    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

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    Contact us

    +44 (0)1334 46 2344
    School of Mathematics and Statistics
    Mathematical Institute
    North Haugh
    St Andrews
    KY16 9SS

    School of Mathematics and Statistics website