Date of
Revision
Date of
Previous
Revision
Programme Specification
A programme specification is required for any programme on which a student may be
registered.
All programmes of the University are subject to the University’s Quality Assurance
and Enhancement processes as set out in the DASA Policies and Procedures Manual.
Programme Title
Programme Code
Mathematics and
Statistics & Operational
Research
MTHBSC-JS,
MTH-JSSOR
UCAS
Code
Final Award
BSc Joint Honours
(exit route if applicable for
Postgraduate Taught
Programmes)
GG13
JACS
Code
Criteria for Admissions
Stage 1 Entry: 3 A-levels ABB (or equivalent) grade A Mathematics
(Please see General Regulations)
Mode of Study (Full-time, Part-time, other)
Full-time
Type of
Programme
BSc Joint Honours –
Mathematics &
Statistics & Operational
Research
Length of
Programme
Total
Credits for
Programme
3 Years
Awarding Institution/Body
Queen's University Belfast
Teaching Institution
QUB, School of Mathematics and Physics
School/Department
School of Mathematics and Physics
Framework for Higher Education
Qualification Level
FHEQ Level 6
360
http://www.qaa.ac.uk/publications/informationan
dguidance
QAA Benchmark Group
http://www.qaa.ac.uk/AssuringStandardsAndQ
uality/subject-guidance/Pages/Subjectbenchmark-statements.aspx
Mathematics, Statistics and Operational Research
Collaborative Organisation and form of
Collaboration (if applicable)
Accreditations
(PSRB)
Date of next
scheduled
accreditation visit
2018
ATAS Clearance
External Examiner Name:
External Examiner Institution/Organisation
Professor D A Jordan (Pure Maths)
University of Sheffield
Professor J Fyodorov (Applied Maths)
Queen Mary, University of London
Dr G Taylor (Statistics & Operational Research)
University of Bath
Does the Programme have any approved
exemptions from the University General
Regulations
Yes
(Please see General Regulations)
Programme Specific Regulations
□
No
X
(If yes, please state here any exemptions to regulations which have
been approved for this programme)
Examinations
Candidates who have completed an Honours Pathway to
the satisfaction of the examiners shall be placed in one of
three honours classes, first, second and third, the second
class being in two divisions.
When calculating the honours classification the following
module weightings are used –
Stage 1
Stage 2
Stage 3
10%
30%
60%
Candidates who do not achieve marks sufficient to be
awarded third class honours may be eligible for an Ordinary
BSc degree.
Transfers to Other Pathways
At the end of Stage 2, students maintaining a weighted
average of at least 55% may transfer to the MSci Pathway
in Mathematics & Statistics and Operational Research
Students may transfer to other Pathways (BSc, or if they
have achieved a weighted average of at least 55%, MSci),
provided they have passed all the compulsory modules on
the Pathway to which they are transferring up to that time of
transfer.
Progression
Stage 1
Students will normally take six modules (or their equivalent)
at Level 1 or above. Students must have passed at least five
Stage 1 modules in order to progress to Stage 2.
Stage 2
Students will normally take six modules (or their equivalent)
at Level 2 or above. Students must have passed at least five
Stage 2 modules, and all six Stage 1 modules, in order to
progress to Stage 3.
Students with protected characteristics
.
Are students subject to Fitness to Practise
Regulations
Please indicate Yes/No
(Please see General Regulations)
Length of Programme
Fitness to Practise programmes are those which permit
students to enter a profession which is itself subject to
Fitness to Practise rules
3 YEARS
Educational Aims of Programme On completion of the programme the student will be able to:
To provide a high quality education in Mathematics and Statistics & OR.
To provide opportunities for a balanced and coherent education in Mathematics and Statistics & OR, while retaining students' right to choose their modules flexibly according to
their aptitudes and interests.
To convey the elegance and usefulness of Mathematics and Statistics & OR.
To develop students' knowledge and skills base in ways which, inter alia, will enhance their employment opportunities and enable them to make a valuable contribution to
society.
To develop students' power of critical analysis.
To enhance students' skills in solving problems from a variety of contexts, using both analytic and computational methods.
To develop the skill of communicating mathematics and mathematical results to others.
To develop students' ability to function professionally as statisticians after graduation.
Learning Outcomes: Cognitive Skills
On the completion of this course successful students will have
Teaching/Learning Methods and Strategies
Methods of Assessment
developed their ability to:
think logically;
By its nature, mathematics has to be presented
The assessment of these skills is implicit
logically. The lectures provide exemplars of this
in all forms of assessment, but is not
process,
as
do
the
model
answers
for
the
explicitly measured. The overall degree
analyse problems and situations;
assignments. Applications of theory are
of success achieved by each student
discussed in lectures and in problems classes or
reflects the extent to which these skills
choose the appropriate mathematics or statistics needed for the
tutorials, in a manner, which brings out the need
have been acquired.
solution of those problems;
to call upon a range of mathematical and
statistical skills in order to solve a problem. The
carry out structured organisation of their work;
use of targeted assignments requires students to
organise their work, sometimes collaboratively
learn independently, under guidance.
but mostly independently.
Learning Outcomes: Transferable Skills
On the completion of this course successful students will have
developed:
skills of analytic thinking and critical analysis;
organisational skills and time management;
presentational skills, in both written and oral form, of mathematical,
statistical, graphical and tabular material;
the ability to work independently;
the ability to meet deadlines.
Teaching/Learning Methods and Strategies
Methods of Assessment
Analytic thinking and critical analysis permeate
any study of the mathematical sciences and
therefore all forms of assessment.
All students are required to make a short
oral presentation of some aspect of their
work. Guidance is provided and the
presentation is assessed. Most of the
assessment, in examinations as in
dissertations, is based on students’
written presentation. Feedback on
assignment submission is designed partly
to enhance the students’ skills in this
area.
Students will only be successful if they plan their
own timetables of work, outside formal classes,
to maintain a balance between their different
modules and between study and other pursuits.
Much of their work is done individually, though in
one project-based module, team working is
encouraged and assessed.
Learning Outcomes: Knowledge and Understanding
On the completion of this course successful students will have
developed knowledge and understanding of:
basic methods and techniques of calculus and analysis, algebra, vector
methods, numerical methods, basic probability, statistical and
operational research methods;
the use of these basic techniques in areas of application, such as
classical mechanics, fluid mechanics, numerical analysis, statistical
inference, operational research;
the importance and development of mathematical rigour, in providing
secure proofs of mathematical statements;
a selection of more specialist optional topics to include areas of
statistics and operational research, as well as pure mathematics and
applied mathematics.
Learning Outcomes: Subject Specific Skills
On the completion of this course successful students will have
developed
a broad range of subject-specific skills in statistics and operational
research and in at least one of pure mathematics or applied
mathematics;
a high level of numeracy;
their ability to construct rigorous mathematical proofs;
an ability to construct computer programs in languages such as
MATLAB or MATHEMATICA to aid the solution of mathematically
based problems;
an ability to use statistical packages such as SAS;
their ability to formulate situations in mathematical or statistical terms,
and to express the solutions in mathematical or statistical problems in
the context in which problems were originally posed;
an awareness of ways in which mathematics, statistics and operational
research are of importance in the world of work.
Teaching/Learning Methods and Strategies
Methods of Assessment
Lectures constitute the foundation for the
presentation of the knowledge and
understanding required of successful students.
These are augmented by a range of measures –
tutorials, problems classes, practical classes –
as appropriate.
Assignments, comprising sets of questions
relevant to the material recently covered in
lectures, and normally set at weekly intervals,
form the major vehicle for a student’s learning of
the various areas of mathematics. Assignments
submitted are marked within one week and
returned to the students to provide individual
feedback on progress. Model answers to all
assignments are made available to students
For the most part, the assignments do
not contribute to the assessment: they
are part of the learning process rather
than the assessment process.
Assessment is mainly through formal
examinations, either at the end of each
module or in class tests held during the
module. In some modules, practical work
is assessed. In the context of project
work, knowledge and understanding are
assessed through the write-up or
dissertation.
Teaching/Learning Methods and Strategies
Methods of Assessment
Mathematical skills are acquired through doing
and applying mathematics. While lectures
provide a basis for this process, it is the
undertaking of the weekly assignments, which is
the key vehicle for developing a breadth and
depth of mathematical ability. Confidence is
thereby engendered, and this is enhanced
through discussion in tutorials and problems
classes. Practical classes develop skills in the
use of mathematical and statistical software and
the solution of problems for which an analytic
approach does not lead to a full solution.
We link closely with the University
Careers Service who provides lectures
and workshops involving employers of
mathematicians and statisticians.
Assessment is through formal
examinations, practical assignments and
project dissertations.
Programme Requirements
Module Title
Module
Code
Level/
stage
Credits
Availability
S1
Duration
Pre-requisite
S2
Assessment
Core
Option
Coursework %
Examination %
10
90
At Stage 1 Students are required to take six compulsory modules.
Vector Algebra & Dynamics
AMA1001
I
20
12 Weeks
A-level Maths B
Numbers, Sets and
Sequences
PMA1012
I
20
12 Weeks
A-level Maths B
Introduction to Probability
and Operational Research
SOR1001
I
20
12 Weeks
A level Maths B
Waves and Vector Fields
AMA1002
I
20
12 Weeks
AMA1001 (corequisite)
Analysis and Linear Algebra
PMA1014
I
20
12 Weeks
Statistical Methods
SOR1002
I
20
12 Weeks
A-level Maths B
PMA1012 (corequisite)
SOR1001 (corequisite)
100
10
90
20
80
100
10
90
Module Title
Module
Code
Level/
stage
Credits
Availability
S1
Duration
Pre-requisite
S2
Assessment
Core
Option
Coursework
Examination
At Stage 2 Students are required to take an approved combination of six modules from those available in Applied Mathematics, Pure Mathematics, Statistics & OR, to include
SOR2002 and at least one of SOR2003 and SOR2004.
A student intending to take more than one module of Applied Mathematics at Stage 3 must pass the examination in at least two of the AMA modules.
A student intending to take more than one module of Pure Mathematics at Stage 3 must pass the examination in at least two of PMA2002, PMA2008 and PMA2007.
Normally no student shall be permitted to take more than two of AMA2003, PMA2003 and PMA2007.
AMA2001
AMA1001 and
Classical Mechanics
20
12 Weeks
II
AMA1002
100
Methods of Applied
Mathematics
AMA2003
II
20
12 Weeks
None
Complex Variables
PMA2003
II
20
12 Weeks
PMA1014
Linear Algebra
PMA2007
II
20
12 Weeks
PMA1012 and
PMA1014
Elementary Number Theory
PMA2010
II
20
12 Weeks
None
Statistical Inference
SOR2002
II
20
12 Weeks
SOR1002
Numerical Analysis
AMA2004
II
20
12 Weeks
None
Fluid Mechanics
AMA2005
II
20
12 Weeks
AMA1002
Analysis
PMA2002
II
20
12 Weeks
PMA1014
Group Theory
PMA2008
II
20
12 Weeks
PMA1012 and
PMA1014
Geometry
PMA2009
II
20
12 Weeks
None
Methods of Operational
Research
SOR2003
II
20
12 Weeks
SOR1001
Linear Models
SOR2004
II
20
12 Weeks
SOR2002 (corequisite)
100
100
100
100
30
70
40
60
100
100
100
10
90
100
Module Title
Module
Code
Level/
stage
Availability
S1
Duration
Pre-requisite
S2
Assessment
Core
Option
Coursework
Examination
At Stage 3 Students must take an approved combination of modules of total Students must take an approved combination of six modules from those available at Level 3 in Applied Mathematics, Pure
Mathematics and Statistics & OR, to include the equivalent of at least two full modules from Statistics & Operational Research. No more than one Project module may be chosen. Both PMA4013 and PMA3014
are intended primarily for students on the MSci Mathematics pathway.
AMA3001
None
Electromagnetic Theory
20
12 Weeks
III
100
Quantum Theory
AMA3002
III
20
12 Weeks
None
Advanced Numerical
Analysis
Partial Differential Equations
AMA3004
III
20
12 Weeks
AMA2004
AMA3006
III
20
12 Weeks
None
Computer Algebra
PMA3008
III
20
12 Weeks
None
Ring Theory
PMA3012
III
20
12 Weeks
PMA2007
Set Theory
PMA3014
III
20
12 Weeks
PMA2007
Convergence
PMA3016
III
20
12 Weeks
PMA2002 (or
PMA2003
100
Linear & Dynamic
Programming
Stochastic Processes
SOR3001
III
20
12 Weeks
AMA1001 or
PMA1012
100
SOR3012
III
20
12 Weeks
SOR1001
Statistical Data Mining
SOR3008
III
20
12 Weeks
SOR2004
Tensor Field Theory
AMA3003
III
20
12 Weeks
None
Financial Mathematics
AMA3007
III
20
12 Weeks
None
Calculus of Variations &
Hamiltonian Mechanics
Mathematical modelling in
biology and medicine
Computer Algebra
AMA3013
III
20
12 Weeks
None
AMA3014
III
20
12 Weeks
None
PMA3008
III
20
12 Weeks
None
Mathematical Investigations
PMA4013
III
20
12 Weeks
None
Metric and Normed Spaces
PMA3017
III
20
12 Weeks
PMA2002
Algebraic Equations
PMA3018
III
20
12 Weeks
PMA2008 & either
PMA2007 or
AMA2003
100
30
70
100
100
100
100
100
15
85
100
100
100
100
100
100
100
100
Approved by Director of Education:
Print Name: ……………………………………………………..
Signature: …………………………………………
Date: ……………………………..