Statistical Ecology (PGDip/MSc) 2020 entry
In this course, you will learn the modern statistical methods currently used by professionals in ecology. You will learn 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.
Postgraduate, leading to a Postgraduate Diploma (PGDip) or Master of Science (MSc)
- Start date: 7 September 2020
- End date: 30 June 2021 (PGDip) or 30 September 2021 (MSc)
Ten months full time (PGDip); one year full time or two years part time (MSc)
You should have the following qualifications:
- 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.
UK and EU: £9,450
Wednesday 12 August 2020. Applicants should apply as early as possible to be eligible for certain scholarships and for international visa purposes.
- personal statement (optional)
- two original signed academic references
- academic transcripts and degree certificates
- evidence of English language proficiency (required if English is not your first language).
For more guidance, see supporting documents and references for postgraduate taught programmes.
The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2019-2020 academic year; some elements may be subject to change for 2020 entry.
Students typically take the following five 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.
- 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.
- Estimating Animal Abundance and Biodiversity: introduces the main types of survey methods for wildlife populations.
- Computing in Statistics: teaches computer programming skills, including principles of good programming practice, with an emphasis on statistical computing.
- 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.
- Statistical Problem Solving: focuses on problem formulation and scientific reporting to a variety of audiences; it consists of a set of case studies covering a range of application
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
All students are recommended to include one of the following two modules in their choices:
- Multivariate Analysis
- Advanced Data Analysis
Optional modules are subject to change each year, and 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 modules listed here are indicative, and there is no guarantee they will run for 2020 entry. Take a look at the most up-to-date modules in the module catalogue.