UNIVERSITY OF YORK UNDERGRADUATE PROGRAMME REGULATIONS · 2 Educational aims of the programme The BA/BSc Mathematics and Statistics programme aims to foster and develop students

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UNIVERSITY OF YORK

UNDERGRADUATE PROGRAMME REGULATIONS

This document applies to students who commence the programme(s) in:

October 2013

Awarding institution Teaching institution

University of York University of York

Department(s)

Mathematics

Award(s) and programme title(s) Level of qualification

BA/BSc (Hons) in Mathematics and Statistics Level 6/Honours

Interim awards available

Certificate of Higher Education (Level 4/Certificate) Generic

Diploma of Higher Education (Level 5/Intermediate) Generic

Length and status of the programme(s) and mode(s) of study

Programme Length (years) and status (full-time/part-time)

Mode

Face-to-face, campus-based

Distance learning

Other

BA/BSc in Mathematics and Statistics

3 years full-time Yes No N/A

Programme accreditation by Professional, Statutory or Regulatory Bodies (if applicable)

N\A

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Educational aims of the programme

The BA/BSc Mathematics and Statistics programme aims to foster and develop students' mathematical and Statistical accomplishment, principally in their:

1. awareness of the scope, achievements and possibilities of mathematics and Statistics;

2. understanding of the logical processes necessary to establish mathematical and Statistical truth, and ability to think logically and analytically;

3. competence and confidence in the use of appropriate mathematical and Statistical tools, techniques and methodologies for solving and/or analysing a wide range of problems;

4. preparedness for a career requiring a high level of numeracy, or further mathematics/Statistics-related study (including, but not limited to, postgraduate courses in mathematics and Statistics education);

5. readiness to take their place in an educated public, contribute a specific outlook and way of thinking to society at large, and continue to pursue mathematical and Statistical interests for pleasure and intellectual reward.

Intended learning outcomes for the programme – and how the programme enables students to achieve and demonstrate the intended learning outcomes

This programme provides opportunities for students to develop and demonstrate knowledge and understanding qualities, skills and other attributes in the following areas:

The following teaching, learning and assessment methods enable students to achieve and to demonstrate the programme learning outcomes:

A: Knowledge and understanding

Knowledge and understanding of:

1. A broad range of mathematical ideas and structures, from pure mathematics, mathematical physics, applied mathematics, applied statistics, numerical and computational mathematics and statistics, and mathematical finance.

2. Some of the great mathematical and Statistical achievements of humanity.

3. A range of mathematical and Statistical techniques for use in technical, professional or financial occupations.

4. One or more of the computer packages currently available for symbolic manipulation of mathematical and Statistical expressions, implementation of algorithms, and numerical evaluation of mathematical and statistical functions and processes.

5. The essential definitions in a wide range of mathematical and statistical theories.

6. The arguments required to prove a wide variety of mathematical and Statistical theorems.

7. The significance of mathematical and Statistical theorems, by means of appropriate consequences, examples and applications.

8. The practical use of mathematical and Statistical theorems to provide a range of problem-solving techniques.

9. The application of appropriate techniques to solve

Learning/teaching methods and strategies (relating to numbered outcomes):

lectures (1-11)

seminars (1-11)

examples classes

practical classes (4)

directed independent study (2,11)

Departmental VLE (Moodle) (1-11)

Types/methods of assessment (relating to numbered outcomes):

weekly/fortnightly exercises (1-11) (Note: Mathematics modules use assignments purely as formative modes of assessment)

closed examinations (1-3, 5-11)

open book examinations (4)

project dissertation (2)

project poster (11)

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a variety of problems.

10. The processes of mathematical and Statistical abstraction and generalisation, whereby specific examples and problems generate new mathematical and Statistical theory.

11. The effective communication of mathematics and Statistics.

B: (i) Skills - discipline related

Able to:

1. Engage in inductive and deductive mathematical and Statistical reasoning, to the point where major mathematical and Statistical theorems may be deconstructed, and unseen (minor) mathematical and Statistical theorems may be successfully formulated and proved.

2. Apply a range of mathematical and Statistical techniques to successfully solve unseen problems in pure and applied mathematics, applied statistics, numerical and computational mathematics and Statistics, and possibly financial mathematics.

3. Analyse complex problems into simpler sub-problems.

4. Accurately transmit mathematical and Statistical information and ideas.

5. Conduct an independent investigation of an advanced (H-level) area of statistics, and present the results of such investigation in mathematically and Statistically formal written form, using appropriate mathematical typesetting software (LaTeX).

6. Use a general purpose computer algebra program (Maple), along with appropriate discipline-specific computer software packages (for example, R, Matlab).

7. Communicate mathematics and Statistics to a wider audience.


seminars (1-4, 7)

examples classes (1-3)

practical classes (5,6)

directed independent study (5)


weekly or fortnightly assignments (1-4, 6) (see above)

coursework of a more extended nature (5,6)

project dissertation (4,5)

project poster (7)

B: (ii) Skills - transferable

Able to:

1. Think logically, precisely and critically.

2. Analyse technical problems.

3. Solve such problems.

4. Work in a collegial environment, when required.

5. Work independently, when required.

6. Organise and manage a workload involving rapidly changing goals and demands.

7. Communicate coherently on both small and large


seminars (1-4, 7)

weekly or fornightly exercises (formative aspects) (1-7)

practical classes (9)

directed independent study (5,8)

Departmental VLE (Moodle) (4, 6-9)

Types/methods of assessment (relating to

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scales, in written, spoken and graphical forms.

8. Gather information, both in electronic and printed form.

9. Routinely use electronic means of transferring and manipulating data, from e-mail and the world wide web to specialised computer packages and programs.

numbered outcomes):

weekly or fortnightly coursework assignments (1-7) (see above)

project dissertation (5,8,9)

project poster (7)

C: Experience and other attributes

Able to:

1. Assess and filter information "on the fly", and make accurate records for future reference.

2. Summarise and evaluate information presented in lectures, in a timely and reflective manner.

3. Participate constructively in small group learning.

4. Adopt a flexible approach to workload management.

5. Work to deadlines and manage time effectively.

6. Routinely analyse and reflect on personal performance and achievement.

7. Identify goals for personal development, and formulate plans to achieve them.

8. Identify future career pathways.


lectures (1,2)

seminars (3,6)

coursework (4,5)

personal development planning (6-8)


Not directly assessed

Relevant Quality Assurance Agency benchmark statement(s) and other relevant external reference points (e.g. National Occupational Standards, or the requirements of Professional, Statutory or Regulatory bodies)

QAA Benchmark Statement for Mathematics, Statistics, and Operational Research:

http://www.qaa.ac.uk/academicinfrastructure/benchmark/statements/Maths07.asp

The Institute of Actuaries:

http://www.actuaries.org.uk/__data/assets/pdf_file/0010/148708/FandI_CT8_2010_syl.pdf

University award regulations

To be eligible for an award of the University of York a student must undertake an approved programme of study, obtain a specified number of credits (at a specified level(s)), and meet any other requirements of the award as specified in the award requirements, programme information, and other University regulations (e.g. payment of fees). Credit will be awarded upon passing a module’s assessment(s) but some credit may be awarded where failure has been compensated by achievement in other modules. The University’s award and assessment regulations specify the University’s marking scheme, and rules governing progression (including rules for compensation), reassessment, award requirements and degree classification. The award and assessment regulations apply to all programmes: any exceptions that that relate to this programme are approved by University Teaching Committee and are recorded at the end of this document.

Departmental policies on assessment and feedback

Detailed information on assessment (including grade descriptors, marking procedures, word counts etc.) is available in the written statement of assessment which applies to this programme and the relevant module descriptions. These are available in the student handbook and on the Department’s website: http://maths.york.ac.uk/www/HandbookAssess

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Information on formative and summative feedback to students on their work is available in the written statement on feedback to students which applies to this programme and the relevant module descriptions. These are available in the student handbook and on the Department’s website: http://maths.york.ac.uk/www/HandbookAssess

Are electives permitted? Upto 20 credits of electives may be taken in each of Stages 2 and 3.

Can a Languages For All (LFA) module be taken ab initio (i.e. beginner level) in Stage 1?

No.

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Diagrammatic representation of the programme structure by stage, showing the distribution and credit value of core and option modules

Stage 1

Autumn Term Spring Term Summer Term

Calculus (30, core)

Core Algebra (30, core)

Introduction to Probability and Statistics (20, core)

Introduction to Applied Mathematics (20, core)

Real Analysis (20, core)

Stage 2


Optional modules from table 2A (30)

Introduction to Group Theory (10, core)

Linear Algebra (20, core)

Statistics I (10, core) Complex Analysis and Integral Transforms (20, core)

Applied Probability (10, core) Statistics II (20, core)

Stage 3


BA/BSc Project (40, core) (statistics-related)

Bayesian Statistics (10, core) Financial Time Series (10,

core)

Generalised Linear Models (10, core) Multivariate Analysis (10,

core)

Optional modules from table 3A (20) Optional modules from table 3B (20)

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Overview of modules by stage

Stage 1 Core module table

Module title Module code

Credit level

1

Credit value

2

Prerequisites

Assessment rules

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Timing and format of main assessment

(AuT – Autumn Term, SpT- Spring Term, SuT – Summer Term)

Calculus 4/C 30 None None 1.5 hr closed multiple choice exam (wk1 SpT); 2.5 hour closed exam (wks 5-7 SuT);

Core Algebra 4/C 30 None None 1.5 hr closed multiple choice exam (wk1 SpT); 3 hour closed exam (wks 5-7 SuT);

Introduction to Probability and Statistics (IPS)

4/C 20 None None 3 hour closed exam (wk1 SpT);

Introduction to Applied Mathematics (IAM)

4/C 20 Calculus (AuT material), Core Algebra (AuT material)

None 3 hour closed exam (wks 5-7 SuT); assessed coursework

Real Analysis 4/C 20 Calculus (AuT material), Core Algebra (AuT material)

None 3 hour closed exam (wks 5-7 SuT);

1 The credit level is an indication of the module’s relative intellectual demand, complexity and depth of learning and of learner autonomy (Level 4/Certificate, Level

5/Intermediate, Level 6/Honours, Level 7/Masters) 2 The credit value gives the notional workload for the module, where 1 credit corresponds to a notional workload of 10 hours (including contact hours, private study

and assessment) 3 Special assessment rules

P/F – the module marked on a pass/fail basis (NB pass/fail modules cannot be compensated) NC – the module cannot be compensated NR – there is no reassessment opportunity for this module. It must be passed at the first attempt

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Credit level

Credit value

Prerequisites

Assessment rules


Statistics I 5/I 10 IPS None 1.5 hour closed exam (wk1 SpT);

Applied Probability 5/I 10 IPS None 1.5 hour closed exam (wk1 SpT);

Introduction to Group Theory (IGT) 5/I 10 Core Algebra None 1.5 hour closed exam (wk1 SpT);

Statistics II 5/I 20 Statistics I None 3 hour closed exam (wks 5-7 SuT);

Complex Analysis and Integral Transforms (CAIT)

5/I 20 Calculus, Real Analysis


Linear Algebra 5/I 20 Core Algebra None 3 hour closed exam (wks 5-7 SuT);

Option module tables. Students choose 30 credits from Table 2A. Table 2A


Credit level

Credit value

Prerequisites

Assessment rules


Differential Equations 5/I 10 Calculus None 1.5 hour closed exam (wk1 SpT);

Introduction to Number Theory (INT) 5/I 10 Core Algebra None 1.5 hour closed exam (wk1 SpT);

Vector Calculus 5/I 20 Calculus, Core Algebra


Groups, Rings and Fields (GRF) 5/I 20 IGT None 3 hour closed exam (wks 5-7 SuT);

Classical Mechanics 5/I 20 IAM None 3 hour closed exam (wks 5-7 SuT);



Credit level

Credit value

Prerequisites

Assessment rules


BA/BSc Project 6/H 40 Dependent on project title

NR: coursework and poster are not reassessable, the

Assessed coursework (AuT, SpT); dissertation (wk4 SuT); poster presentation (wk8 SuT)

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dissertation is reassessable

Financial Time Series 6/H 10 Statistics I None 2 hour closed exam (wk5-7 SuT);

Generalised Linear Models 6/H 10 Statistics II None 2 hour closed exam (wk1 SpT);

Bayesian Statistics 6/H 10 Statistics II None 2 hour closed exam (wk 1 SpT);

Multivariate Analysis 6/H 10 Statistics II, Linear Algebra


Option module tables. Students choose 40 credits; normally 30 credits from Table 3A and 30 credits from Table 3B. Students are permitted to take 30 credits from Table 3A and 10 credits from Table 3B if they so wish. Students wishing to take 10 credits from Table 3A and 30 credits from Table 3B will require approval from the Mathematics Board of Studies. Not more than 2 of the Table 3B modules “Algebraic Number Theory”, “Lebesgue Integration”, “Special Functions” may normally be taken, due to an element of front loading in these modules. 3rd year BSc students may, with the permission of the Chair of Board of Studies, take up to 20 credits of M-level modules, subject to their 2nd year stage-average being at 60% or above, The list below is indicative as options can vary from year to year. Options for the following year are normally confirmed near the beginning of the Spring term. Students should be aware that it is not always possible to select all combinations of options due to timetabling constraints. Table 3A


Credit level

Credit value

Prerequisites

Assessment rules


Metric Spaces 6/H 10 Real Analysis None 2 hour closed exam (wk1 SpT);

Galois Theory 6/H 10 Linear Algebra, GRF, Intro to Group Theory

None 2 hour closed exam (wk1 SpT);

Dynamics of Inviscid Fluids 6/H 10 Vector Calculus, Differential Equations


Formal Languages and Automata 6/H 10 IGT None 2 hour closed exam (wk1 SpT);

Differential Geometry 6/H 10 Vector Calculus, Linear


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Algebra

Special Relativity 6/H 10 Calculus, Core Algebra, IAM, Vector Calculus


Quantum Mechanics I 6/H 10 Calculus, Linear Algebra, Classical Mechanics


Introduction to Dynamical Systems 6/H 10 Differential Equations


Stochastic Processes 6/H 10 Applied Probability


Mathematical Finance I 6/H 10 Statistics I, Linear Algebra


C++ Programming for Mathematicians

6/H 10 Generic Stages 1 & 2

None 3 hour open book exam (wk10 SpT);

Cryptography 6/H 10 Intro to Number Theory


Statistical Pattern Recognition 6/H 10 Statistics I, Statistics II


Maths in Science and Society 6/H 10 None None Presentation (SpT); Essay

Table 3B


Credit level

Credit value

Prerequisites

Assessment rules


Lebesgue Integration 6/H 10 Metric Spaces None 2 hour closed exam (wks 5-7 SuT);

Algebraic Number Theory 6/H 10 GRF None 2 hour closed exam (wks 5-7 SuT);

Special Functions 6/H 10 Differential Equations, CAIT


Lie Algebras 6/H 10 Linear Algebra, GRF


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Number Theory 6/H 10 INT, Real Analysis


Electromagnetism 6/H 10 Vector Calculus, Special Relativity


Quantum Mechanics II 6/H 10 Quantum Mechanics I, CAIT, Vector Calculus, Classical Mechanics


Applications of Group Theory in Virology

6/H 10 Generic Stages 1 & 2


Survival Analysis 6/H 10 Statistics II None 2 hour closed exam (wks 5-7 SuT);

Mathematical Finance II 6/H 10 Math Finance I, Stochastic Processes


Numerical Analysis and Scientific Computing

6/H 10 Calculus, IAM None 1 hour closed exam (wks 5-7 SuT); coursework set during module

Dynamics of Viscous Fluids 6/H 10 Vector Calculus, Dynamics of Inviscid Fluids


Applications of non-linear dynamics 6/H 10 Intro to Dynamical Systems


Biological Fluid Dyanmics 6/H 10 Dynamics of Inviscid Fluids


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Additional year variants e.g. year in Europe, year in industry

Replacement year variants

Students on all programmes may apply to spend Stage 2 on the University-wide North America/Asia/Australia student exchange programme. Acceptance onto the programme is on a competitive basis.

Marks from modules taken on replacement years count toward progression and classification.

Transfers out of or into the programme

Requests to transfer between the BA/BSc Mathematics and statistics programme and one of the various combined Mathematics programmes are dealt with on an individual basis, and are normally only permitted during Stage 1.

Exceptions to University Award Regulations approved by University Teaching Committee

Exception Date approved

None Not applicable

Quality and Standards

The University has a framework in place to ensure that the standards of its programmes are maintained, and the quality of the learning experience is enhanced.

Quality assurance and enhancement processes include:

the academic oversight of programmes within departments by a Board of Studies, which includes student representation

the oversight of programmes by external examiners, who ensure that standards at the University of York are comparable with those elsewhere in the sector

annual monitoring and periodic review of programmes

the acquisition of feedback from students by departments, and via the National Student Survey.

More information can be obtained from the Academic Support Office: http://www.york.ac.uk/admin/aso/teach/

Departmental Statements on Audit and Review Procedures are available at: http://www.york.ac.uk/admin/aso/teach/deptstatements/index.htm

Date on which this programme information was updated:

September 2013

Departmental web page: http://maths.york.ac.uk/www/Home

Please note

The information above provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are

http://www.york.ac.uk/admin/aso/teach/

http://www.york.ac.uk/admin/aso/teach/deptstatements/index.htm

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provided.

Detailed information on the learning outcomes, content, delivery and assessment of modules can be found in the module descriptions.

The University reserves the right to modify this overview in unforeseen circumstances, or where the process of academic development, based on feedback from staff, students, external examiners or professional bodies, requires a change to be made. Students will be notified of any substantive changes at the first available opportunity.

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UNIVERSITY OF YORK UNDERGRADUATE PROGRAMME REGULATIONS · 2 Educational aims of the programme The BA/BSc Mathematics and Statistics programme aims to foster and develop students