> bjbjss i.5xIIIII$mmmPm6Ye#e#4###$$$XXXXXXXZ]TX]I'$$''XII##Xn*n*n*'I#I#Xn*'Xn*n*RX#:,%m(UN}XY06YU"])]XX&]I1XL$v%Tn*Z%D%|$$$XXn*$$$6Y'''']$$$$$$$$$ : A. NATURE OF THE AWARD
Awarding Institution: Kingston University
Programme Accredited by: N/A
Final Award(s): BSc (Hons)
Intermediate Awards: CertHE, DipHE, Ordinary Degree
Field Title: Medical Statistics
FHEQ Level: Honours
JACs code: G300
QAA Benchmark Statement(s): Mathematics, Statistics and Operational Research (QAA 2007)
Minimum Registration: 3 years
Maximum Registration: 9 years
Faculty: Science, Engineering and Computing
School: N/A
Location: Penrhyn Road
Date Specification Produced: February 2005
Date Specification Revised: August 2011
B. FEATURES OF THE FIELD
1. Title:
The field is available in the following forms:
- BSc (Hons) Medical Statistics and x
- BSc (Hons) Medical Statistics with x
- BSc (Hons) x with Medical Statistics
where x is a second subject.
2. Modes of Delivery
The field is offered in the following alternative patterns
- Full time
- Part time
Medical statistics, in its available forms above, is offered as a three year full time course, although it is possible for students to switch between full time and part time mode of attendance. A sandwich option is available.
Features of the Field
Faculty of Computing Information Systems & Mathematics offers a field (with minor, major and half modes) in Medical Statistics (MDS) within the Joint Honours programme of the Undergraduate Modular Scheme (UMS). The MDS field can be combined with fields in Computing, Applied Economics (in minor or half mode), Environmental Studies, Geography, Human Geography, Web Development, Mathematics (in half mode only). In addition the major form combined with the minor in Business leads to a degree in Medical Statistics with Business.
EDUCATIONAL AIMS OF THE FIELD
Throughout the programmes, emphasis is placed on the applications of statistics to medical areas, including practical work using computer packages, whilst retaining the necessary theoretical underpinning. There is provision for the development of a range of transferable skills and to demonstrate ability in applying practical and analytical skills.
The field aims to give students a sound foundation in statistics (together with relevant mathematics and computing), as well as assisting them in their general, personal development by providing them with a coherent, academically-sound programme of study. The field aims to provide a coherent and balanced programme of study to stand alone with a minor, half or major from a second field.
Thus, the first part of the course (level 1 and semester 1 of level 2) is delivered through core modules that cover material that is important to any student obtaining a degree in statistics. Further core modules at level 2 and 3 look at specific statistical techniques used in Medical Statistics and applications of other techniques to the Medical field. These will provide a solid basis for further study. The aim is to provide students with a solid understanding of basic knowledge, ideas and techniques.
The core statistics modules address four themes:-
Basic probability theory and distribution theory;
Data analysis including the use of statistical computer packages;
Basic ideas of statistical modelling;
Application of statistics in the medical field.
Graduates who have followed the MDS field should be well prepared for many opportunities in further academic or professional studies or for employment in hospitals, pharmaceutical companies and other health-related professions.
.
The aims of the MDS field are to develop students abilities to:
attain a body of knowledge and skills in statistics in order to understand the basic principles and methods of the subject, and to apply them successfully in the medical field;
be confident in applying appropriate techniques, including the use of statistical software, to identify, analyse and solve a variety of problems in the medical field;
identify the relationships between various areas in medical statistics;
seek, use and communicate relevant information effectively in oral, visual and written forms;
work both in groups and individually, and to work for and with non-statisticians;
have a broad knowledge of the role of statistics in the medical field, including relevant career opportunities;
extend their knowledge in medical statistics by further formal study (for academic or professional qualifications) or by effective use of published work.
For each module within the field, specific aims are given in the module descriptions.
LEARNING OUTCOMES OF THE FIELD
The learning outcomes of the MDS field are to produce graduates who are able to:
Knowledge and Understanding
demonstrate an appropriate level of understanding and knowledge in
statistics that they are able to apply to a variety of problems in the medical field;
2. Cognitive (thinking) Skills
(a) apply statistical methods to problems in the medical field, from understanding the formulation of the problem to communicating the result of its solution, whilst appreciating the limitations of the methods;
(b) demonstrate research skills;
Practical Skills
(a) analyse and make informative inferences about real-life data, for example that arise from clinical trials;
use modern technology to communicate information effectively;
use relevant computer packages to assist in statistical analysis;
4. Key Skills
Each module has key skills embedded within its main body of work. Students on the field have opportunities to gain a wide range of transferable skills that are developed through the levels. On completion of the field students will have acquired transferable skills to:
(a) Communication Skills
receive and respond to a variety of information e.g. taking part in discussions;
select, extract and collate information from appropriate sources;
present information in a variety of formats/media;
communicate the outcome of their statistical analysis/modelling effectively;
(b) Numeracy
apply numerical skills and techniques to quantitative situations e.g. collect data (where appropriate), assess quantitative data, perform basic calculations and statistical analysis;
(c) Information, Communication and Technology
make effective use of computer systems to aid data manipulation and presentation e.g. presenting different forms of information, effective statistical interpretation of output, searching for and storing information, on-line communication;
(d) Teamwork
work effectively as a member of a team, appreciating the value of their own and others contributions;
(e) Independent Learning
display self management and organisation leading to attainment of objectives within timelines and personal development e.g. developing research, information handling and communication skills, developing self awareness and time-management, monitoring and reviewing own progress.
Table 1 below identifies the key skills associated with summative assessment components for core modules and options. Modules shown in bold are core on all programmes; all other modules are options. It should be recognised that, in addition, students develop these skills extensively away from these summative assessment exercises: in classes, in formative assessment exercises, in private study and in extra-curricula activities.
Table 1 - Key Skills Summary
Module CodeModule TitleCommunicationNumeracyICTTeamworkIndependent LearningCO1000 Fundamental Programming Concepts I, LCI, L, TI, L, TCO2060 DatabasesG(R,O)G(R,O), TG(R,O)EMA1010Mathematical Science IC, GC, G, TGGMA1020Mathematical Science IICC, T, ECEMA1261Mathematical Studies IC,GC, G, T GMA1271Mathematical Studies IICC,T,ECEMA3200Mathematical ProgrammingG(R)G(R), T, EG(R)G(R)G(R), EST1210Introduction to Probability and StatisticsC, TCST1220Introductory Statistical InferenceRR, T, ERR, EST2210Regression ModellingG(R)G(R), T, EG(R)G(R)G(R), EST2220Statistical DistributionsCC, EEST2333Experimental DesignCC, ECC, EST2343Medical StatisticsI(R)I(R), T, EI(R)I(R), EST3310Stochastic ProcessesI(R)I(R), C, EI(R)I(R), C,EST3320Time Series and Forecasting MethodsG(R)G(R), T, EG(R)G(R )G(R), EST3333Experimental DesignCC, ECC, EST3353Operational Research TechniquesCC, ECEST3370Further Inference and Bayesian MethodsCC, EEST3390Statistical Modelling in Medical ResearchI(R)I(R), T, EI(R)I(R), EST3990ProjectD, O, RD, O, RD, O, RDD, O, R
Key:
C - Coursework Assignment, D - Project Development, E Examination,
I - Individual Case Study or Self-Study/Research Exercise,
G - Group Case Study or Self-Study, L - Library Workbook,
O - Oral Presentation/Interview, R Report, T - In-class Test.
The learning and teaching strategies of the field seek to ensure that students learn actively and effectively, thus laying the foundation for future careers and/or further study.
Table 2 Learning Outcomes of the Field
Module CodeModule Title1. Knowledge and Understanding2. Cognitive
(thinking) Skills3. Practical Skills1(a)2(a)2(b)3(a)3(b)3(c)CO1000Fundamental Programming Concepts %CO2060 Databases%MA1010Mathematical Science I%MA1020Mathematical Science II%%MA1261Mathematical Studies I%MA1271Mathematical Studies II%%MA3200Mathematical Programming%%ST1210Introduction to Probability and Statistics%%%%ST1220Introductory Statistical Inference%%%%%ST2210Regression Modelling%%%%%%ST2220Statistical Distributions%ST2333Experimental Design%%%%%%ST2343Medical Statistics%%%%%%ST3310Stochastic Processes%%%%%%ST3320Time Series and Forecasting%%%%ST3333Experimental Design%%%%%ST3353Operational Research Techniques%%%%ST3370Further Inference and Bayesian Methods%%%%%ST3390Statistical Modelling in
Medical Research%%%%%%ST3990Project%%%%%%
E. FIELD STRUCTURE
The MDS field assumes no previous knowledge of statistics, and is presented as a coherent set of modules, providing a balanced programme in theoretical and applied probability and statistics, whilst allowing some option choices in the higher levels. Throughout the emphasis is on the applications of statistics to medicine, including the use of computer packages, to real-life problems, whilst retaining the theoretical underpinning necessary for understanding of the concepts met.
The sandwich year (work placement) is an optional element in the programme, taken between levels 5 and 6. Students who opt for the sandwich mode spend a minimum period of 36 weeks in an approved placement in industry or commerce. The integrated and coherent nature of the field programme ensures that the students have opportunities to gain the necessary prerequisites for all option modules.
Level 4
Each field in a joint degree contributes three modules at level 4, together with a mathematics module and a computing module; the overlap this causes in some courses leads to many students being able to take a free-choice module in the first year, thus enhancing their academic experience.
At level 4, students are introduced to a wide variety of topics, laying the foundation in the necessary mathematics and computing, as well as in statistics, for further work in this field. The modules at this level are common to the minor, half and major modes.
The level of mathematics studied will depend on the choice of the other field. Thus, those on a Joint Mathematics and Medical Statistics degree are required to complete MA1010, MA1020 and MA1030 (Mathematical Sciences I and II and Introduction to Linear Algebra). Students who combine Medical Statistics with one of the other possible fields are required to complete MA1261 and MA1271 (Mathematical Studies I and II).
In the two statistics modules students meet some fundamental concepts in probability and statistics. They also learn techniques, including practical tools, with which to apply these concepts to various problems, some of which are in the medical field.
It is to be noted that, there is no formal examination at the end of semester A at level 4, and the modules in that period are assessed by in-course assessment.
The modules to be taken are:
Semester A
CodeModule TitleCore/OptionST1210Introduction to Probability & StatisticsCoreMA1010 or
MA1261Mathematical Science I or
Mathematical Studies ICoreCO1000Fundamental Programming ConceptsCore
Semester B
CodeModule TitleCore/OptionST1220Introductory Statistical Inference
CoreMA1020 or
MA1271Mathematical Science II or
Mathematical Studies IICore
Level 5
There are three core modules in level 5 two in the first semester and one in the second semester. Each of the first semester modules develops themes met in ST1210 and the one in the second semester has ST2210 as a pre-requisite.
ST2210, Regression Modelling, extends knowledge of simple linear regression to multiple linear and logistic regression; here also students learn to use SAS. In ST2220, Statistical Distributions, students gain further knowledge of discrete and continuous distributions, including joint distributions and parameter estimation. In ST2343, Medical Statistics, students are introduced to specific statistical techniques used in Medical Statistics and applications of these and other techniques to the medical field.
The modules available are:
Semester A
CodeModule TitleCore/OptionST2210Regression ModellingCoreST2220Statistical DistributionsCore
Semester B
CodeModule TitleCore/OptionST2333Experimental DesignOptionST2343Medical StatisticsCoreCO2060DatabasesOption
Generally, students take 0, 1 or 2 options in semester B, dependent on whether they are taking a minor, half or major field respectively. Computing and Medical Statistics combinations take CO2060 Databases as part of the Computing field and so can choose from the remaining two options.
Level 6
There is one core module, ST3390, Statistical Modelling in Medical Research, at level 6. This aims to broaden the students knowledge and understanding of statistical methods and their medical research applications. There are also two project modules, which may be solely statistics-based on a medical topic, or of an interdisciplinary nature on a topic which draws on the integration of both fields studied. The remaining modules are options.
The modules available are:
Semester A
CodeModule TitleCore/OptionST3320Time Series and Forecasting MethodsOptionST3390Statistical Modelling in Medical ResearchCoreMA3200Mathematical ProgrammingOptionMA3991Issues in Mathematics EducationOption
Semester B
CodeModule TitleCore/OptionST3310Stochastic ProcessesOptionST3333Experimental DesignOptionST3353Operational Research TechniquesOptionST3370Further Inference & Bayesian MethodsOptionMA3992Mathematics in the ClassroomOption
Generally, students will take 2, 3 or 4 options at level 6, dependent on whether they are taking a minor, half or major field respectively.
F. FIELD REFERENCE POINTS
The Field has been designed to take account of QAA Subject Benchmark Statements for MSOR (QAA 2007).
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.
Module content, especially at level 6, is informed by staff research expertise, and other scholastic activities and employment experience.
TEACHING AND LEARNING 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 important areas in medical statistics 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, hence leaving 95 hours or 106 hours of self-directed or guided study time respectively. There is a higher level of 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 most 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 modules have an associated study guide or textbook 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 on Study Space (the universitys learning management system) or in hard copy. The Faculty produces KU tables which give basic mathematical and statistical formulae and a number of statistical tables; these may be used in lectures, in problems classes and in tests or examinations.
Students are 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 are given regular formative exercises or practical work through which they can develop learning skills, knowledge and techniques. Further they 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.
A particularly important component of the degree is the project, which develops the students confidence and ability to carry out group and/or individual pieces of research or scholarship and then communicate their results in both written and oral forms. The project may be solely statistics-based on a topic in medical statistics, or of an interdisciplinary nature, on a topic which draws on the integration of both fields studied.
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; it is designed 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 and end-of-module examination. No module is assessed by an end-of-module examination alone. 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 field 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 answered 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 (not applicable to semester1, level 4 modules).
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 points 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 or group 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 medical statistics or of the second field 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 hand-writing.
Assessment Procedures
It is Faculty 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 externally. 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 3 indicates the methods of assessment to be used. Modules shown in bold are core on all programmes; all other modules are options in this field. Further details are given in the module descriptions in the Module Directory.
Semester 1 modules at level 4 are assessed internally only and there is no end-of-module examination at that stage. The ST and Mathematics for Statistics modules in semester 2 of level 4 are weighted at 50% in-course assessment and 50% examination. At levels 5 and 6 the weightings for the ST modules are 40% coursework, 60% examination, except for ST2210, Regression Modelling, which is 60% coursework, 40% examination, to reflect the practical nature of this module and the fact that this is where SAS is introduced.
Table 3 - Assessment Summary (Indicative)
ModuleTestsWritten assignmentsPractical/
Case StudyExaminationLevel 4CO1000 **MA1010**(Group)MA1020***MA1261 **MA1271****ST1210 **ST1220 ***Level 5CO2060 ** (Group)*ST2210** (Group)*ST2220 ***ST2333**ST2343*** Level 6MA3200**ST3310***ST3320* (Group)*ST3390***ST3333* *ST3353**ST3370**
There are also project modules ST3990 Single and Double semester(s).
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:
For the Medical Statistics Field 260 points, including two 6-unit awards, with at least a GCSE grade B in mathematics 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 MDS field graduate is equipped for employment, for example, as:
- Medical statistician
- Statistician in the pharmaceutical industry
- Researcher in the medical field
Public and private sector managers in medically- related companies
Statistical forecasters
Business analysts for the medical sector
Scientific professions related to medicine
Marketing, sales and advertising professions related to medicine
Teaching in Medical Statistics departments of large hospitals.
K. INDICATORS OF QUALITY
External examiners report, reviewed by Faculty Course Quality Assurance Committee (annual)
QAA MSOR Subject Review (2000).
L. APPROVED VARIANTS FROM THE UMS/PCF
No variations from UMS required.
BSc (JOINT HONOURS) MEDICAL STATISTICS Major Field CJMDSW
LEVEL 4LEVEL 5LEVEL 6
Introduction to Probability & Statistics
ST1210 (E)
GCSE Mathematics B
Introductory Statistical
Inference
ST1220 (C )
ST1210
Regression Modelling
ST2210 ( B )
ST1210, MA1271
Medical Statistics
ST2343 (F)
ST2210
Statistical Modelling
In Medical Research
ST3390 (C )
ST2343
ST Option 3B
Mathematical Studies I
MA1261
GCSE Mathematics B or Equivalent
Mathematical Studies II
MA1271 (D )
MA1261
Statistical Distributions
ST2220 ( E )
ST1210 , MA1261
Experimental Design
ST2333 (E)
ST2210
ST Option 3A
ST Option 3B
Fundamental Programming Concepts
CO1000 (B)
Second Field Module
Second Field Module
Databases
CO2060 (G)
CO1000
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Project or MA3991 Issues in Mathematics Education (D)
A-Level Maths, Level 5
Project or MA3992 Mathematics in the Classroom )
A-Level Maths, Level 5ST Option 3A
ST3320 Time Series & Forecasting Methods (E) ST2210
MA3200 Mathematical Programming (B ) MA1271, CO1000
ST Option 3B
ST3310 Stochastic Processes (C ) MA1271, ST2220
ST3333 Experimental Design (E) ST2210
ST3353 Operational Research Techniques ( F ) MA1271, ST1210
ST3370 Further Inference and Bayesian Methods (G ) ST1210, ST2220
March 2009
BSc (JOINT HONOURS) MEDICAL STATISTICS Half Field CJAMDS
LEVEL 4LEVEL 5LEVEL 6Introduction to Probability & Statistics
ST1210 (E)
GCSE Mathematics BIntroductory Statistical Inference
ST1220 (C)
ST1210Regression Modelling
ST2210 ( B )
ST1210, MA1271Medical Statistics
ST2343B (F)
ST2210Statistical Modelling
In Medical Research
ST3390 (C)
ST2343ST Option 3BMathematical Studies I
MA1261 (D)
GCSE Mathematics B or Equivalent
Mathematical Studies II
MA1271 (D )
MA1261
Statistical Distributions
ST2220 ( E )
ST1210 , MA1261ST Option 2BST Option 3A
Or
Second Field ModuleSecond Field Module
Or
ST Option 3BFundamental Programming Concepts
CO1000 (B)
Second Field ModuleSecond Field ModuleSecond Field ModuleSecond Field ModuleSecond Field ModuleSecond Field Module
Second Field ModuleSecond Field ModuleSecond Field ModuleProject or
MA3991 Issues in Mathematics Education (D)
A-Level Maths, Level 5
Project or MA3992 Mathematics in the Classroom ( )
A-Level Maths, Level 5
Note: At level 6 three Statistics modules, three Second Field modules and two Project modules must be taken
ST Option 2B
ST2333 Experimental Design (E) ST2210
CO2060 Databases (G) CO1000
ST Option 3A
ST3320 Time Series & Forecasting Methods (E) ST2210
MA3200 Mathematical Programming (B) MA1271, CO1000
ST Option 3B
ST3310 Stochastic Processes (C) MA1271, ST2220
ST3333 Experimental Design (E) ST2210
ST3353 Operational Research Techniques (F)
MA1271, ST1210
ST3370 Further Inference & Bayesian Methods (G)
ST1210, ST2220 March 2009
BSc (JOINT HONOURS) MEDICAL STATISTICS Minor Field CJ.WMDS
LEVEL 4LEVEL 5optionalLEVEL 6
Introduction to Probability
& Statistics
ST1210 (E)
GCSE Mathematics B
Introductory Statistical Inference
ST1220 (C)
ST1210
Regression Modelling
ST2210 ( B )
ST1210, MA1271
Medical Statistics
ST2343B (F)
ST2210
Industrial Placement Year
Statistical Modelling
In Medical Research
ST3390 (C)
ST2343
ST Option 3B
Mathematical Studies I
MA1261 (D)
GCSE Mathematics B or Equivalent
Mathematical Studies II MA1271 (D)
MA1261
Statistical Distributions
ST2220 ( E )
ST1210 , MA1261
Or
Second Field Module
Second Field
Module
Or
ST Option 2B
Second Field
Module
Second Field
Module
Fundamental Programming Concepts
CO1000 (B)
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Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Second Field
Module
Project
Project
ST Option 2B
ST2333 Experimental Design (E) ST2210
CO2060 Databases (G) CO1000
ST Option 3B
ST3310 Stochastic Processes (C ) MA1271, ST2220
ST3333 Experimental Design (E) ) ST2210
ST3353 Operational Research Techniques ( F )MA1271, ST1210
ST3370 Further Inference & Bayesian Methods (G) ST1210, ST2220
March 2009
PROGRAMME SPECIFICATION KINGSTON UNIVERSITY
Medical Statistics, major, half and minor fields, BSc (Hons) 2011-12
PAGE
Page PAGE 1 of NUMPAGES 15
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