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Statistics (Including Placement Year)

Course overview

(BSc) Bachelor of Science
Statistics (Including Placement Year)
University of Essex
University of Essex
Mathematical Sciences
Colchester Campus
This programme will meet the educational requirements of the Chartered Mathematician designation, awarded by the Institute of Mathematics and its Applications, when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught masters degrees.
Honours Degree
Mathematics, Statistics and Operational Research
BSC 9K13

A-levels: BBB, including Mathematics
Please note we are unable to accept A-level Use of Mathematics in place of A-level Mathematics

IB: 30 points, including Higher Level Mathematics grade 5. We are also happy to consider a combination of separate IB Diploma Programmes at both Higher and Standard Level.

Exact offer levels will vary depending on the range of subjects being taken at higher and standard level, and the course applied for. Please contact the Undergraduate Admissions Office for more information.

English language requirements for applicants whose first language is not English: IELTS 6.0 overall. Different requirements apply for second year entry, and specified component grades are also required for applicants who require a Tier 4 visa to study in the UK.

Other English language qualifications may be acceptable so please contact us for further details. If we accept the English component of an international qualification then it will be included in the information given about the academic levels listed above. Please note that date restrictions may apply to some English language qualifications

If you are an international student requiring a Tier 4 visa to study in the UK please see our immigration webpages for the latest Home Office guidance on English language qualifications.

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

If you’re an international student, but do not meet the English language or academic requirements for direct admission to this degree, you could prepare and gain entry through a pathway course. Find out more about opportunities available to you at the University of Essex International College here.

External Examiners

Prof Fionn Murtagh
Professor of Data Science

External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment. External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course. They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards. External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.

eNROL, the module enrolment system, is now open until Monday 21 October 2019 8:59AM, for students wishing to make changes to their module options.


Core You must take this module You must pass this module. No failure can be permitted.
Core with Options You can choose which module to study
Compulsory You must take this module There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Compulsory with Options You can choose which module to study
Optional You can choose which module to study

Year 1 - 2019/20

Component Number Module Code Module Title Status Credits
01 MA101-4-FY Calculus Core 30
02 MA114-4-AU Matrices and Complex Numbers Core 15
03 MA182-4-AU Numerical Methods and Computation Compulsory 15
04 CE152-4-SP Object-Oriented Programming Compulsory 15
05 MA108-4-SP Statistics I Core 15
06 MA181-4-AU Discrete Mathematics Compulsory 15
07 CE151-4-AU Introduction to Programming Compulsory 15
08 MA199-4-FY Mathematics Careers and Employability Compulsory 0

Year 2 - 2020/21

Component Number Module Code Module Title Status Credits
01 MA201-5-AU Linear Algebra Compulsory 15
02 MA200-5-AU Statistics II Core 15
03 MA216-5-SP Survival Analysis Core 15
04 MA203-5-AU Real Analysis Compulsory 15
05 MA209-5-SP Numerical Methods Compulsory 15
06 MA205-5-SP Optimisation (Linear Programming) Compulsory 15
07 CE213-5-AU Artificial Intelligence Compulsory 15
08 MA199-5-FY Mathematics Careers and Employability Compulsory 0
09 MA202-5-SP Ordinary Differential Equations Compulsory 15

Year Abroad/Placement - 2021/22

Component Number Module Code Module Title Status Credits
01 MA100-6-FY Placement Year Compulsory 120

Year 3 - 2022/23

Component Number Module Code Module Title Status Credits
01 MA318-6-AU Statistical Methods Core 15
02 MA321-6-SP Applied Statistics Core 15
03 MA317-6-AU Modelling Experimental Data Core 15
04 MA199-6-FY Mathematics Careers and Employability Compulsory 0
05 MA319-6-AU Stochastic Processes Compulsory 15
06 MA831-6-FY or MA830-6-AU or MA830-6-SP plus one option from list Compulsory with Options 30
07 Option(s) from list Optional 15
08 MA304-6-AU Exploratory Data Analysis and Data Visualisation Compulsory 15

Exit awards

A module is given one of the following statuses: 'core' – meaning it must be taken and passed; 'compulsory' – meaning it must be taken; or 'optional' – meaning that students can choose the module from a designated list. The rules of assessment may allow for limited condonement of fails in 'compulsory' or 'optional' modules, but 'core' modules cannot be failed. The status of the module may be different in any exit awards which are available for the course. Exam Boards will consider students' eligibility for an exit award if they fail the main award or do not complete their studies.

Programme aims

Mathematics and Statistics is a degree designed for mathematicians who are oriented towards applying their skills into understanding and analysing data using modern statistical methods.

Its teaching aims are to equip students with an equivalent level of mathematical and statistical knowledge and skills that are currently in demand in statistically oriented employment in business, commerce, industry, government service, health, the field of education and in the wider economy; to provide students with a foundation for further study, research and professional development; to produce graduates who are mathematically and statistically literate and capable of appreciating a logical argument; to produce graduates who can perform data analysis, understand randomness and sampling; to provide teaching which is informed and enhanced by the research activities of the staff.

Learning outcomes and learning, teaching and assessment methods

On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:

A: Knowledge and understanding

A1 Knowledge and understanding of the basic mathematical methods and techniques of linear mathematics, calculus and statistics that underpin the study of more advanced mathematical ideas.
A2 Knowledge and understanding of some of the ideas and methods used in mathematical proof of results in algebra, analysis, and discrete mathematics and familiarity with some specific examples.
A3 Knowledge and understanding of the power and potential pitfalls of computer use and mathematical computer packages, and experience in their use.
A4 Knowledge and understanding of the use of mathematics for modelling and as an investigative tool for the solution of practical problems. An appreciation of the importance of assumptions.
A5 Knowledge and understanding of the use of probability and statistics for research methods, data analysis, hypothesis testing and statistical modelling.
A101 Experience of mathematics and statistics in industry
Learning Methods: Lectures are the principal method of delivery for the concepts and principles involved in A1-A5.

Students are also directed to reading from textbooks and material available online.

In some modules, understanding is enhanced through the production of a written report.

Understanding is reinforced by means of classes (A1-A5), laboratories (A3, A4, A5) and assignments (A1-A5).
The 3rd year of this 4- year course is spent in industry (A101).
Assessment Methods: Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations, and also, in some modules, through marked coursework, laboratory reports, statistical assignments, project reports and oral examinations (A1-A5).

Regular problem sheets provide formative assessment in all modules.

Methods employed to assess knowledge and understanding of statistics include: class presentations, written coursework, project work and class tests.
A101 is demonstrated by successful completion of the year spent in industry.

B: Intellectual and cognitive skills

B1 Identify an appropriate method to solve a specific mathematical problem.
B2 Analyse a given mathematical problem and select the most appropriate tools for its solution.
B3 Identify data from relevant sources.
B4 Evaluate evidence.
B5 Perform statistical data analysis.
Learning Methods: The basis for intellectual skills in mathematics modules is provided in lectures, and the skills are developed by means of recommended reading, guided and independent study, assignments and project work.

B1 and B2 are developed through exercises supported by classes.

B1 and B2 are all-important aspects of the projects that constitute a part of some modules and the optional final year project.

B3 to B5 are acquired through group projects assignments and analysis of authentic materials in class; laboratory work involving use of dedicated software collection of data and online materials.
Assessment Methods: Achievement of intellectual skills in mathematics modules is assessed primarily through unseen closed-book examinations, and also through marked assignments and project work (B1 and B2).

Methods employed to assess knowledge and understanding statistics include: class presentations, written coursework, project work and class tests.

C: Practical skills

C1 Use computational tools and packages.
C2 The ability to apply a rigorous, analytic, highly numerate approach to a problem.
C3 Organising and presenting data.
C4 Gathering and processing information from different sources.
Learning Methods: The practical skills of mathematics and statistics are developed in exercise classes, laboratory classes, assignments and project work.

C1 is acquired through the learning of at least one programming language and the use of a number of computer packages, as a part of the teaching of modules for which they are relevant.

C2 is acquired and enhanced throughout the course.

C3 is acquired through such methods as group discussion of topical themes and analysis of authentic materials in class, laboratory work involving use of dedicated software and online materials and staff advice, feedback and interaction with students.

C4 is acquired and enhanced throughout the course.
Assessment Methods: Achievement of practical skills C1 and C2 is assessed through marked coursework, project reports and oral examinations.

Methods employed to assess practical skills C3 and C4 typically include class presentations, written coursework, written exams, class tests and web-based assignments.

D: Key skills

D1 Communicate effectively mathematical arguments, and ideas and information in the chosen language.
D2 Use appropriate IT facilities as a tool in the analysis of mathematical problems, word processing, finding modern language materials etc.
D3 Use mathematical techniques correctly.
D4 Analyse complex problems and find effective solutions.
D5 Collaborate with others to work creatively and flexibly as part of a team
D6 Working autonomously showing organisation, self-discipline and time management
Learning Methods: D1 is practised throughout the course in the writing of solutions to mathematical problems, both for assessment and as exercises.

D2 is developed through the use of computer packages in a number of mathematics and statistics modules.

D3 and D4 are developed and enhanced in all mathematics modules.

D5 is developed in various mathematics and statistics modules, through exercises and assessments.

D6 is developed and enhanced throughout the course of the degree.
Assessment Methods: D1 is assessed through coursework and oral examinations.

D2 is assessed primarily through coursework.

Assessment of the key skills D3 and D4 is intrinsic to subject-based assessment in mathematics.

D5 is assessed through group work in various mathematics and language modules.

Assessment of key skill D6 is mainly through successful submission of coursework.


The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Should you have any questions about programme specifications, please contact Course Records, Quality and Academic Development; email: