> } u{bjbj55 i__r?????$cccP,Lc2W+%A%4u%u%u%T&'<>' VVVVVVV$$Y[TV?(P&T&((V??u%u%V)/)/)/(p?u%?u%V)/(V)/)/]NlQu%|?c)O*VW02WO\*\TQ\?Q^'0'")/''^'^'^'VV,^'^'^'2W((((\^'^'^'^'^'^'^'^'^' : A. NATURE OF THE AWARD
Awarding Institution: Kingston University
Programme Accredited by:
Final Award(s): BSc (Hons)
Intermediate Award(s): CertHE; DipHE, Ordinary Degree
Field Title: Actuarial Mathematics and Statistics
FHEQ Level for the final award: Honours
Credit rating by level: 120 @ level 4, 120 @ level 5, 120 @ level 6, 60 @ level P
JACs code: G100
QAA Benchmark Statement(s): The Actuarial Mathematics and Statistics field described below complies with the MSOR subject benchmark statement (QAA 2007).
Minimum Period of Registration: 3 years full time, 4 years with placement
Maximum Period of Registration: 9 years full time, 10 years with placement
Faculty: Computing, Information Systems and Mathematics
School: N/A
Location: Penrhyn Road
Date Specification Produced: March 2010
Date revised: June 2010
B. FEATURES OF THE FIELD
1. Title:
The field is available in the following forms:
BSc (Hons) Actuarial Mathematics and Statistics
2. Modes of Delivery
The field is offered in the following alternative patterns:
- Full time
- Part time
- Sandwich
Actuarial Mathematics and Statistics is offered as a three year full time course, although it is possible for students to study for the degree in part-time mode. Students may switch between full time and part time modes of attendance. A sandwich option is also available.
3. Features of the Field
The Faculty of Computing, Information Systems and Mathematics (CISM) offers a full field in Actuarial Mathematics and Statistics, leading to the BSc degree in Actuarial Mathematics and Statistics, within the Undergraduate Modular Scheme (UMS). The field covers the fundamental mathematical and statistical methods required by students interested in solving practical problems, particularly those related to the Actuarial Profession, together with the development of the necessary analytical skills. The field constitutes a coherent, academically sound programme of study which will assist students in their general personal development and produce graduates suited for employment in careers associated with the insurance, financial and actuarial professions. It will also prepare graduates for further study in a wide variety of areas where mathematical, statistical and/or financial economics skills are used, or for employment in any field where these skills, or more generic analytical skills, are valued. Embedded within the provision is the opportunity for the development of a range of other key skills, to further extend and enhance career opportunities and development.
The vocational nature of the field and its relation to the courses offered by the Institute and Faculty of Actuaries for professional accreditation has been recognised in the design of the field. The core modules cover major portions of the courses CT1, CT3, and CT5 and much of CT6 as described at HYPERLINK "http://www.actuaries.org.uk" www.actuaries.org.uk. It is possible to cover the major portions of other courses offered by the Institute and Faculty of Actuaries (CT2, CT4 and CT8) through careful choice of option modules.
The Actuarial Mathematics and Statistics field shares a common level 4 curriculum with the Actuarial Science field which enables transfer between the fields at the end of the first year for students who achieve a mark of at least 50% in every module at first attempt.
The curriculum at levels 5 and 6 enables students to pursue the study of financially based mathematics but also encompasses a broader range of topics to allow those students not fully committed to a single career path to develop other interests and expertise.
EDUCATIONAL AIMS OF THE FIELD
The Actuarial Mathematics and Statistics field aims are to develop students abilities to:
a) attain a body of knowledge and skills in mathematics and statistics and the ability to apply them to a range of problems (with particular emphasis on those in financial areas);
b) identify relationships between the various subject areas they have studied;
c) seek, use and communicate relevant information effectively in oral, visual and written forms;
d) work in groups and individually;
e) extend their knowledge in the relevant subject areas by further formal study (for academic or professional qualifications) or by effective use of published work.
Specific aims for each module within the field are given in the module descriptions.
D. LEARNING OUTCOMES (OBJECTIVES) OF THE FIELD
The learning outcomes of the Actuarial Mathematics and Statistics field are to produce graduates who are able to:
1. Knowledge and Understanding
1 demonstrate knowledge of appropriate mathematical, statistical and financial principles and techniques and apply them to a variety of problems;
2. Cognitive (thinking) Skills
2a formulate problem solutions;
2b identify appropriate techniques based on theory and practice in Mathematics, Statistics or Finance to solve problems related to the management of financial risk;
2c demonstrate research skills.
3. Practical Skills
3 solve practical problems associated with the Financial, Banking and Insurance industry being aware of relevant computer software to assist in the solution of practical problems;
4. Key Skills
On completion of the field students will have acquired the following key skills to:
a. Self awareness skills
display self management and organisation leading to attainment of objectives within timelines and personal development;
monitor and review own progress;
b. Communication skills
receive and respond to a variety of information e.g. taking part in discussions; selecting, extracting and collating information from appropriate sources; presenting information in a variety of formats/media;
c. Interpersonal skills
work effectively as a member of a team, appreciating the value of their own and others contributions;
d. Creativity and problem solving
develop mathematical intuition and use a variety of approaches to find, evaluate and justify solutions to problems;
e. Research and information literacy skills
make effective use of computer systems to aid data manipulation and presentation e.g. presenting different forms of information; searching for and storing information; on-line communication;
f. Numeracy
apply numerical skills and techniques to quantitative situations e.g. collecting data (where appropriate); evaluating quantitative data; performing basic calculations
g. Management and leadership skills
determine the scope of extended tasks and allocate time and other resources to enable completion within the given deadline.
Table 1 below identifies the key skills associated with summative assessment components for core modules (bold text) and options in this field. It should be recognised that, in addition, students will be developing these skills extensively away from these assessment exercises: in classes, in formative tasks, in private study and in extra-curricula activities.
The learning and teaching strategies of the field seek to ensure that students learn actively and effectively, thus laying the foundation for future careers, particularly in the finance industry, and/or further study.
Self awareness skillsCommunication skillsInterpersonal skillsCreativity and problem solvingResearch and information literacy skillsNumeracyManagement and leadership skillsSelf managementprogressLevel 4MA1015XXXXXXXMA1030XXXXXMA1050XXXXXXST1220XXXXXXST1810XXXXXST1820XXXXST1830XST1840XXXCO1000XXXXXLevel 5MA2010XXXXMA2020XXXXMA2030XXXXXXXMA2040XXXXXXXXST2210XXXXXXXXST2220XXXXXST2353XXXXXXST2810XXXXXST2820XXXXXST2890XXXXXXXXCO2040XXXXLevel 6MA3010XXXXXXMA3090XXXXXXXXMA3170XXXXMA3130XXXXXXMA3200XXXXXXXXMA3210XXXXXXXXMA3991XXXXXXMA3992XXXXXXXMA3995/
MA3990XXXXXXXXST3310XXXXXXXST3320XXXXXXXST3370XXXXXST3810XXXXXST3820XXXXXXST3830XXXXXX
Table 1 Key Skills Summary
E. FIELD STRUCTURE
The structure of the field is indicated on the attached course diagram. The modules at each level total to a credit value of 120 credits.
The placement year is an optional element in the programme, taken between levels 5 and 6. Students who opt for the sandwich mode will spend a minimum period of 36 weeks in an approved placement in industry or commerce. The placement allows students to gain an insight into business and how it works, as well as developing key interpersonal skills and giving extra self-confidence for when they finish their degrees and start their careers. It also gives students the opportunity to apply their technical and problem solving skills to practical problems and provides them with an understanding of the role of their course in the real world, away from the lecture theatre.
Level 4
At Level 4, students will be introduced to a wide variety of topics, laying the necessary foundation for further work in the course. The study of mathematical methods will include calculus, linear algebra, ordinary differential equations, an introduction to numerical methods and exposure to symbolic algebra and linear algebra packages. Core statistics modules are included to underpin and to provide pre-requisites for later options. In the statistics module students will meet some fundamental concepts in probability and statistics, as well as be provided with the techniques, including practical tools, with which to apply these concepts to various problems. ST1820 is a core module in financial mathematics which introduces compound interest functions and annuities and forms the basis for later actuarial modules.
In the first Semester 1 significant proportion of the content of MA1015 is designed to overlap selected A-level material in accordance with the aim of widening participation. No previous knowledge of Statistics is assumed.
All level 4 modules are shared with the field in Actuarial Science. This is a specific design feature which enables transfer between two fields at the end of Level 4.
The level 4 modules contributing to the field are:
Semester 1
Module TitleCodeCREDITSIntroduction to Probability & Statistics AST181015Fundamental Programming Concepts (option)CO100015Modern Techniques for Mathematics (option)MA105015Introduction to Economics (option)ST183015Financial Management for Actuaries (option)ST184015
Semester 2
Module TitleCodeCREDITSIntroduction to Linear AlgebraMA103015Introductory Statistical InferenceST122015
Semesters 1&2
Module TitleCodeCREDITSIntroduction to Mathematical AnalysisMA101530Mathematics of Finance and InvestmentST182030
Level 5
Seven core modules will run through the field at level 5. The first semester module, Concepts of Mathematics, will ensure that students engage in logical argument, mathematical proof and the modelling cycle whilst enhancing their communication skills. The Mathematical Methods module will build on the Level 4 work, introducing additional techniques and providing a foundation for numerical and analytical treatments of ordinary and partial differential equations later in the course. The study of ordinary differential equations is extended to systems in the second semester where a symbolic algebra package (MAPLE) will be used to assist qualitative understanding with graphical representations. ST2210, Regression Modelling, extends knowledge of simple linear regression to multiple linear and logistic regression and the students also learn to use the Statistics software package SAS. In ST2220, Statistical Distributions, students gain further knowledge of discrete and continuous distributions, including joint distributions and parameter estimation. Survival Models, ST2810 provides statistical applications to lifetime distributions and estimation of mortality rates. Finally, there is an option in the second semester where students can choose to branch into a mathematical specialism or to aim towards further actuarial exemptions by selecting the module on Risk Models.
The level 5 modules contributing to the field are:
Semester 1
Module TitleCodeCREDITSMathematical Methods MA201015Concepts of MathematicsMA203015Regression ModellingST221015Statistical DistributionsST222015
Semester 2
Module TitleCodeCREDITSOrdinary Differential Equations MA202015Operational Research TechniquesST235315Survival Models ST281015Risk Models (option)ST282015Mathematical Modelling I (option)MA204015Fortran Programming (option)CO204015
Level 6
There are three core modules and four options at level 6. The options enable students to concentrate on studying towards further actuarial exemptions or to broaden mathematical and statistical knowledge including further specialisation in mathematical modelling or fluid dynamics. There is also a possibility to do an individual project (15 credits in one semester or 30 credits over two semesters). Two mathematical education modules, one theoretical and the other work-based in a local school or college, are offered as an alternative to a project to those students who are considering a career in education.
The level 6 modules contributing to the field are:
Core Modules:
Semester 1
Module TitleCodeCREDITSPartial Differential Equations and Approximation TheoryMA301015
Semester 2
Module TitleCodeCREDITSFurther Inference & Bayesian MethodsST337015
Semesters 1&2
Module TitleCodeCREDITSContingenciesST381030
Option Modules:
Semester 1
Module TitleCodeCREDITSMathematical Modelling IIMA309015Mathematical ProgrammingMA320015Issues in Mathematical EducationMA399115ProjectMA399015Stochastic ProcessesST331015Time Series and Forecasting MethodsST332015Portfolios and InvestmentsST382015
Semester 2
Module TitleCodeCREDITSFluid Dynamics in ActionMA317015Optimisation MA313015Introduction to Calculus of Variations and Optimal Control MA321015Mathematics in the ClassroomMA399215Project MA399015Market Models and Derivative SecuritiesST383015
Semesters 1&2
Module TitleCodeCREDITSProjectMA399530
F. FIELD REFERENCE CREDITS
In designing the field cognisance has been taken of the relevant portions of the associated benchmark statement for Mathematics, Statistics and Operational Research (MSOR).
The awards made to students who complete the field or who are awarded intermediate qualifications comply fully with the National Qualifications Framework.
All of the procedures associated with the field comply with the QAA Codes of Practice for Higher Education.
As previously mentioned the vocational nature of the field and its relation to the courses offered by the Institute and Faculty of Actuaries for professional accreditation has been recognised in the design.
G. LEARNING AND TEACHING STRATEGIES
The learning and teaching strategies reflect the field aims and learning outcomes, student background, potential employer requirements and the need to develop a broad range of technical skills, with the ability to apply them appropriately. The strategies ensure that students have a sound understanding of some relevant areas in mathematics, statistics and financial economics and have acquired the transferable skills expected of modern-day undergraduates.
150 hours of study time is allocated to each module. Typically, this includes 55 hours of contact time per module at level 4 and 44 hours at levels 5 and 6, leaving the remainders for self-directed or guided study time. There is more contact at level 4 to provide initial academic support and students are encouraged to develop as independent learners as they progress through their degree course. Contact time can consist of lectures, tutorials, problems classes, practicals or PAL sessions, dependent on individual module requirements. Generally, subject material and corresponding techniques will be introduced in lectures; for many modules, practical activities are regarded as essential to the understanding of the material and the development of relevant skills. In problems classes students typically work through formative exercises under guidance and in PAL sessions second year students help those at level 4 to develop their study skills.
Some level 4 MA modules have an associated study guide containing core material and formative exercises, the remainder have these materials distributed throughout the semester.. These materials, and worksheets in computing practical sessions, help develop self-paced learning and independent study. Most higher level modules have lecture notes available in hard-copy or on StudySpace, which is the universitys learning management system. The faculty produces KU Tables, which give basic mathematical and statistical formulae and a number of statistical tables; these may be used in lectures, problem classes, tests or examinations.
Students will be expected to develop their skills, knowledge and understanding through independent and group learning, in the form of both guided and self-directed study. In most modules students will be given regular formative exercises or practical work through which they can develop learning skills, knowledge and techniques. Further they will have the opportunity to work individually and in groups on assignments, practicals, case studies and projects. These activities and their assessment are designed to enable students to meet the specific learning outcomes of the field.
H. ASSESSMENT STRATEGIES
Assessment enables students abilities to be measured in relation to the aims of the field; assessment also serves as a means for students to monitor their own progress at prescribed stages and enhance the learning process.
The assessment strategy has been devised to reflect the aims of the field and to complement the learning and teaching strategies described above. Throughout the field students are exposed to a range of assessment methods, thus allowing them to develop technical and key skills and enabling the effectiveness of the learning and teaching strategies to be evaluated.
The methods of assessment have been selected so as to be most appropriate for the nature of the subject material, teaching style and learning outcomes in each module. Some modules are assessed entirely by in-course work, while others have, in addition an end-of-module examination. In particular, the balance between the various assessment methods for each module reflects the specified learning outcomes.
The assessments are designed so that students achievements of the fields learning outcomes can be measured. A wide range of assessment techniques will be used to review as accurately and comprehensively as possible the students attainments in acquiring sound factual knowledge together with the appropriate technical competence and understanding, so that they can tackle various types of problems.
Components of Assessment
In the field as a whole, the following components may be used in the assessment of the various modules:
- Multiple choice or short answer in-class tests: to assess competence in basic techniques and understanding of concepts
- Long answer structured questions in coursework assignments: to assess ability to apply learned techniques to solve simple to medium problems and which may include a limited investigative component
- Long answer structured questions in end-of-module examinations: to assess overall breadth of knowledge and technical competence to provide concise and accurate solutions within restricted time
- Practical exercises: to assess students understanding and technical competence
- Individual case studies: to assess ability to understand requirements and to provide solutions to realistic problems. The outcomes can be:
- Written report, where the ability to communicate the relevant concepts, methods, results and conclusions effectively will be assessed.
- Oral presentation, where the ability to summarise accurately and communicate clearly the key credits from the work in a brief presentation will be assessed.
- Group-based case studies: contain all of the assessment objectives of individual case studies and in addition to assess ability to interact and work effectively with others as a contributing member of a team
- Project: The individual project module is similar to an extended case study. The problems tackled may be of a more open-ended nature, allowing students to increase their knowledge of actuarial mathematics and statistics by studying a topic in greater depth and/or by applying techniques learned in a new situation. As such the assessment here will place a greater emphasis on ability to plan work, manage time effectively, and research background information, although students will also be expected to produce written reports and to be interviewed about their work.
In addition to any specific criteria, the following features are expected in work that is submitted for coursework assignments:
- Technical competence: the generated system or solution performs the requirements stated in the best possible implementation.
- Completeness: all aspects of the work are attempted and full explanations of all reasoning are given.
- Clarity: all explanations are clear and concise. Arguments follow a logical sequence and are laid out in a clear format.
- Neatness: all reports are produced using a word-processor. Tables, graphs and diagrams are neat and suitably labelled. Assignments with a high mathematical content may be submitted in neat handwriting.
Assessment Procedures
It is policy that in-course work is returned to students within three working weeks. Feedback can be model solutions and/or comments on the work. All examination papers, coursework and tests are internally moderated and those for levels 5 and 6 also reviewed externally by external examiners. Projects are double-marked; examination scripts are checked to ensure that all work has been marked and scores correctly totalled.
The formal assessment procedure is specified in the general regulations of the UMS.
Assessment Summary
Table 2 indicates the methods of assessment to be used in all the modules. Further details are given in the module descriptions.
Table 3 shows the distribution of the field learning outcomes across its core and option modules.
Module TitleCodeTestsWritten
AssignmentsPractical/
Case StudyExaminationLevel 4Introduction to Mathematical AnalysisMA1015***Introduction to Linear AlgebraMA1030***Modern Techniques for MathematicsMA1050**Introductory statistical InferenceST1220***Introduction to Probability & Statistics AST1810***Mathematics of Finance and InvestmentST1820**Fundamental Programming ConceptsCO1000**Introduction to EconomicsST1830*Financial Management for ActuariesST1840**Level 5Mathematical Methods MA2010**Ordinary Differential Equations: Analytical and Computational MethodsMA2020**Concepts of MathematicsMA2030*Mathematical Modelling IMA2040***(Group)Regression ModellingST2210**(Group)Statistical DistributionsST2220***Operational Research TechniquesST2353**Survival ModelsST2810**Risk ModelsST2820**Fortran ProgrammingCO2040**Level 6Partial Differential Equations and Approximation TheoryMA3010**Mathematical Modelling IIMA3090***(Group)Optimisation MA3130**Fluid Dynamics in Action (A)MA3170**Mathematical ProgrammingMA3200**Introduction to Calculus of Variations and Optimal Control Theory MA3210**Project MA3990/5*Issues in Mathematical EducationMA3991**Mathematics in the ClassroomMA3992**Stochastic ProcessesST3310***Time Series and Forecasting MethodsST3320*(Group)*Further Inference & Bayesian MethodsST3370**ContingenciesST3810**Portfolios and InvestmentsST3820**Market Models and Derivative SecuritiesST3830**
Table 2 - Assessment Summary (Indicative)
Field Learning Outcomes12a2b2c3Level 4MA1015Introduction to Mathematical Analysis(((MA1030Introduction to Linear Algebra(((MA1050Modern Techniques for Mathematics((ST1220Introductory Statistical Inference((ST1810Introduction to Probability and Statistics A((ST1820Mathematics of Finance and Investment((((CO1000Fundamental Programming Concepts (ST1830Introduction to Economics(((ST1840Financial Management for Actuaries(((Level 5MA2010Mathematical Methods ((MA2020Ordinary Differential Equations((MA2030Concepts of Mathematics(((MA2040Mathematical Modelling I(((ST2210Regression Modelling((ST2220Statistical Distributions((ST2353Operational Research Techniques((((ST2810Survival Models((((ST2820Risk Models((((ST2890Professional Placement(((CO2040Fortran Programming(Level 6MA3010Partial Differential Equations & Approximation Theory(((MA3090Mathematical Modelling II(((MA3170Fluid Dynamics in Action (A)((MA3130Optimisation((MA3200Mathematical Programming((MA3210Introduction to Calculus of Variations and Optimal Control((MA3990/MA3995Project (((((MA3991Issues in Mathematical Education(MA3992Mathematics in the Classroom(ST3310Stochastic Processes((ST3320Time Series and Forecasting((ST3370Further Inference & Bayesian Methods((ST3810Contingencies((((ST3820Portfolios and Investments(((((ST3830Market Models and Derivative Securities(((((
Table 3 - Field Learning Outcomes
I. ENTRY QUALIFICATIONS
1. The minimum entry qualifications for the field are:
The general entry requirements for the field are those applicable to all programmes within the UMS.
2. Typical entry qualifications set for entrants to the field are:
260 points, including two 6-unit awards, with an A-Level in mathematics (or its equivalent) are normally required.
A foundation year is available for students without formal entry qualifications. Mature applicants and those with qualifications not specified above will be considered individually.
J. CAREER OPPORTUNITIES
In addition to providing a route to studying for higher degrees, the Actuarial Mathematics and Statistics field graduate will be equipped for employment, for example, as:
Commercial, industrial and public sector managers
Business and finance associate professionals
Actuaries
Chartered accountants
Statisticians
Business analysts
Scientific and engineering professionals
Marketing, sales and advertising professionals
Teachers
K. INDICATORS OF QUALITY
External examiners report
Student feedback
Internal (faculty) QA processes
L. APPROVED VARIANTS FROM THE UMS/PCF
To comply with the exemption requirements from the Institute and Faculty of Actuaries the following first semester modules will have a formal, end of module examination:
ST1810, ST1830, ST1840
BSc (HONOURS) ACTUARIAL MATHEMATICS AND STATISTICS CFAMS
LEVEL 4LEVEL 5OPTIONALLEVEL 6Introduction to Mathematical Analysis
MA1015 (D)
Mathematical Methods
MA2010 (D)
MA1015, MA1030Ordinary Differential Equations
MA2020 (C)
MA2010Industrial Placement YearContingencies
ST3810 (A+E)
ST1820,ST2810
Introduction to Probability and Statistics A
ST1810 (E)Introduction to Linear Algebra
MA1030 (A)
MA1015Statistical Distributions
ST2220(E)
ST1810/ST1210, MA1015
Survival Models
ST2810 (A)
ST1820PDEs & Approximation Theory
MA3010 (F)
MA2010, MA2020Further Inference and Bayesian Methods
ST3370 (G)
ST1810/ST1210, ST2220Option 1AIntroductory Statistical Inference
ST1220 (C)
ST1810 or ST1210
Concepts of Mathematics
MA2030 (G)
CO1000,MA1015Operational Research Techniques
ST2353(F)
ST1810/ST1210, MA1030Option 3A
Option 3BMathematics of Finance and Investment
ST1820 (C + B)
Regression Modeling
ST2210 (B)
ST1810/ST1210, MA1030
Option 2BOption 3AOption 3B
Option 1A
CO1000 Fundamental Programming Concepts (B)
MA1050 Modern Techniques for Mathematics (A)
ST1830 Introduction to Economics (B)
ST1840 Financial Management for Actuaries (A)
Option 2B
MA2040 Mathematical Modelling I (B) CO1000, MA2030
ST2820 Risk Models (G) ST1810,ST2220
CO2040 FORTRAN Programming (E) CO1000
Option 3A
MA3200 Mathematical Programming (B) MA1030, CO1000
MA3090 Mathematical Modelling II (E) MA2020, MA2040
ST3320 Time Series & Forecasting Methods (E) ST2210
ST3310 Stochastic Processes ( C ) MA1015, ST1810/ST1210
ST3820 Portfolios and Investments (B)ST1220,MA1015
MA3991 Issues in Mathematical Education (D)
MA3995/MA3990 Project
Option 3B
MA3170 Fluid Dynamics in Action (A) MA3010
MA3130 Optimisation (B) MA2010, MA2020
MA3210 Introduction to Calculus of Variations and Optimal Control (C) MA2010, MA2020
ST3830 Market Models & Derivative Securities (A) ST3820,MA3010
MA3992 Mathematics in the Classroom MA2010, MA2020
MA3995/MA3990 Project18 August 2010
PROGRAMME SPECIFICATION KINGSTON UNIVERSITY
Actuarial Mathematics and Statistics, BSc (Hons) 2010-2011
PAGE
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