Masters Degrees in Applied Statistics, United Kingdom

Overview

The MSc Statistics and Applied Probability is suitable for students who wish to broaden and deepen their knowledge in both statistics and applied probability.

The course offers you the opportunity to further your knowledge in both of these areas, which will be beneficial for a professional career in statistics or as a solid basis for research in statistics or applied probability.

Topics include advanced stochastic processes, queueing processes, epidemic models and reliability, as well as most of those listed for the MSc Statistics.

This course is accredited by the Royal Statistical Society

Key facts:

- This course is informed by the work being carried out in the Statistics and Probability research group.

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 60 full-time academic staff.

- In the latest independent Research Assessment Exercise, the School ranked 8th in the UK in "research power" across the three subject areas within the School of Mathematical Sciences (Pure Mathematics, Applied Mathematics, Statistics and Operational Research).

- This course is accredited by the Royal Statistical Society.

Modules

Advanced Stochastic Processes

Applications of Statistics

Computational Statistics

Fundamentals of Statistics

Medical Statistics

Statistics Dissertation

Time Series and Forecasting

Topics in Biomedical Statistics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information

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Our MSc in Operational Research and Applied Statistics aims to equip you with the necessary analytical skills, methods and ways of thinking to tackle and analyse complex organisational problems, help make better decisions, and to become confident statistical analysts.

This course is ideal training and experience for those looking for career opportunities in areas such as Operational Research, management science, statistics, management consultancy, business analytics, supply chain management, government operational research/statistics.

You will undertake case studies and project work which will give you the opportunity to put your skills into practice and provides valuable experience of working in the field. The dissertation project, typically undertaken with an industrial partner, will allow you to work with complex data in a creative manner and a problem-solving environment, as well as to communicate your ideas and findings effectively.

Distinctive features:

• Available on a one year full-time or three year part-time basis

• Acquire transferable operational research and statistical skills that are highly sought after in a broad range of sectors

• Learn from experts in the fields of Operational Research and Statistics

• Gain valuable work experience; we have some placement opportunities available with industrial partners in the UK and abroad

Structure

The course can be completed in one year with full-time study or in three years by part-time study.

The one-year course includes a three-month period working with a company on a real problem that they have identified. You will take 80 credits of core modules and 40 credits of optional modules in the taught component of the programme. This is followed by a 60 credit summer project.

As a part-time student you will typically need to be in the University for lectures and workshops for the equivalent of one day per week over 24 weeks each year. You will usually complete the taught component of the programme over two years with up to a further year to complete the project dissertation.

The programme will prepare you with essential techniques in Operational Research and Applied Statistics, and then allow you to select from optional courses in topics such as supply chain modelling, healthcare, and Statistics and Operational Research for Government (delivered with input from the Office for National Statistics and Welsh Assembly Government).

You will have the opportunity to put the theory into practice, through case studies and project work in the ‘real-world’. An important feature of the MSc is the project dissertation, allowing you to work with an external company.

For a list of modules for the FULL-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research-and-applied-statistics-msc

For a list of the modules for the PART-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research-and-applied-statistics-msc-part-time

Teaching

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

You will apply the skills you develop through presentations, research assignments, case studies and the summer project.

Assessment

During the course your development will primarily be monitored via tutorial sheets, with other means where appropriate.

Written examinations, often in combination with an in-course element forms overall assessment.

Career Prospects

This programme prepares you for a career in areas such as operational research, management science, statistics, risk analysis, financial modelling, actuarial risk and credit scoring, management consultancy, business analytics, supply chain management, government operational research /statistics.

Our School of Mathematics has well established and strong links with many employers of Operational Researchers and Applied Statisticians, who regularly offer projects and/or recruit our students.

If you prefer to continue on a more academic career pathway, you may choose to continue your studies with a PhD.

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Why this course?

This unique Masters in Applied Statistics in Health Sciences provides an opening to a career as an applied statistician, without having previously studied statistics.

The course is run in collaboration with the Animal and Plant Health Agency (APHA), an Executive Agency of the Department for Environment, Food & Rural Affairs (Defra). Statisticians from APHA, as well as those who have extensive experience in working with the National Health Service in Scotland, will provide lectures based around real-life problems and data from the health sciences.

Although the programme is focused on health, the skill set provided will also equip you with the necessary training to work as an applied statistician in other areas such as insurance, finance and commerce.

What you'll learn

The three modules covered in Semester 1 will equip you with fundamental probability and data analysis skills. In Semester 2 there are four modules, each focusing on a different applied element of being a statistician. The course concludes with a research project that will involve the analysis of a real-life data set.

Programme skills set

On the programme you'll acquire:

• in-depth knowledge of modern statistical methods that are used to analyse and visualise real-life data sets and the experience of how to apply these methods in a professional setting
• skills in using statistical software packages that are used in government, industry and commerce
• the ability to interpret the output from statistical tests and data analyses and communicate your findings to a variety of audiences including health professionals, scientists, government officials, managers and stakeholders who may have an interest in the problem
• problem solving and high numeracy skills that are widely sought after in the commercial sector
• practical experience of statistical consultancy and how to interact with professionals who require statistical analyses of their data
• through the contacts with APHA and NHS staff, an understanding of what it's like to work as an applied statistician in practice including, for example, during disease outbreaks

Facilities

The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and computing laboratories that are state-of-the-art with all necessary software available. You'll also have a common room facility, a modern and flexible area which is used for individual and group study work, and also a relaxing social space.

The Department of Mathematics & Statistics

At the heart of the Department of Mathematics & Statistics is the University’s aim of developing useful learning. We're an applied department with many links to industry and government. Most of the academic staff teaching on this course hold joint-appointments with, or are funded by, other organisations, including APHA, Public Health and Intelligence (Health Protection Scotland), Greater Glasgow and Clyde Health Board and the Marine Alliance for Science and Technology Scotland (MASTS). We bridge the gap between academia and real-life. Our research has societal impact.

Learning & teaching

Classes are delivered by a number of teaching methods:

• lectures (using a variety of media including electronic presentations and computer demonstrations)
• tutorials
• computer laboratories
• coursework
• projects

Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.

Assessment

The form of assessment varies for each class. For most classes the assessment involves both coursework and examinations.

Careers

There are many exciting career opportunities for graduates in applied statistics. The practical, real-life skills that you'll gain means you'll be much in demand in international organisations. A report by the Association of the British Pharmaceutical Industry identified statistics and data mining as “two key areas in which a 'skills gap' is threatening the UK's biopharmaceutical industry.”

Typical employers of statisticians and data analysts include:

• Government
• Health services
• Pharmaceutical companies
• Human, animal, plant and environmental research institutes
• Insurance companies
• Banks
• Internet information providers such as Google
• Retailers

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Our MSc in Operational Research, Applied Statistics and Financial Risk aims to equip you with the necessary analytical skills, methods and ways of thinking to tackle and analyse complex organisational problems, help make better decisions, and to become confident statistical analysts.

This course is ideal training for those who wish to study, in greater depth, risk models, particularly for application to financial markets but also to other sectors. 

You will undertake case studies and project work which will give you the opportunity to put your skills into practice and provides valuable experience of working in the field. The dissertation project, typically undertaken with an industrial partner, will allow you to work with complex data in a creative manner and a problem-solving environment, as well as to communicate your ideas and findings effectively.

Distinctive features:

• This course will give you the opportunity to study risk models in greater depth, particularly those models used in financial markets.

• The skills you will develop are highly transferable for use within industry, business and the public sector.

• The School of Mathematics has excellent links with a number of organisations who employ Operational Researchers, Statisticians and Financial / Risk Modellers

Structure

The course can be completed in one year with full-time study or in three years by part-time study.

This full-time one year course includes a three month period working with a company on a real problem that they have identified.
You will take 110 credits of core modules and 10 credits of optional modules in the taught component of the programme. This is followed by a 60 credit summer project.

As a part-time student you will typically need to be in the University for lectures and workshops for the equivalent of one day per week over 24 weeks each year. You will usually complete the taught component of the programme over two years with up to a further year to complete the project dissertation.

The programme will prepare you with essential techniques in Operational Research and Applied Statistics, and then allow you to select from optional courses in topics such as supply chain modelling, healthcare, and Statistics and Operational Research for Government (delivered with input from the Office for National Statistics and Welsh Assembly Government).

You will have the opportunity to put the theory into practice, through case studies and project work in the ‘real-world’. An important feature of the MSc is the project dissertation, allowing you to work with an external company.


For a list of modules for the FULL-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research,-applied-statistics-and-financial-risk-msc

For a list of the modules for the PART-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research,-applied-statistics-and-financial-risk-msc-part-time

Teaching

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

You will apply the skills you develop through presentations, research assignments, case studies and the summer project.

Assessment

During the course your development will primarily be monitored via tutorial sheets, with other means where appropriate.

Written examinations, often in combination with an in-course element forms overall assessment.

Career Prospects

This programme prepares you for a career in areas such as operational research, management science, statistics, risk analysis, financial modelling, actuarial risk and credit scoring, management consultancy, business analytics, supply chain management, government operational research /statistics.

Our School of Mathematics has well established and strong links with many employers of Operational Researchers and Applied Statisticians, who regularly offer projects and/or recruit our students.

Placements

An important feature of the MSc programme is to undertake a project dissertation. This allows you to apply the methods and skills acquired in the taught programme in a real-world setting, and will typically involve working with a company on a project of importance. Some of these placements will be abroad given our strong international connections. Cardiff School of Mathematics already has well established links with many organisations that employ Operational Researchers, Statisticians and Financial Modellers including Admiral, Nationwide, ONS, Lloyds Banking Group and Ernst and Young amongst others.

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This 2-year, part-time MSc Applied Statistics is accredited by the Royal Statistical Society and has been specially designed to meet the personal and career development needs of people who want to continue working, or gain valuable interning experience, while also studying in the evening. Many of our students, as part of their everyday work, are involved in data analysis, the interpretation of statistics, the optimal design and control of systems, and the modelling and prediction of time-dependent phenomena. They bring a wealth of knowledge and experience into the classroom, and you’ll find yourself surrounded by committed, enthusiastic students from all backgrounds, careers and cultures. This programme is ideal if you are considering a career move into statistics, or if your work already involves aspects of data collection and exploration, the interpretation of statistics, or the modelling and forecasting of time-dependent phenomena.

Over 2 years, in lectures and practical computing sessions, the course covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce and research. The programme proceeds from a strong theoretical background, but it is practically oriented, in order to develop your ability to tackle new and non-standard problems confidently. The mutual dependence of practice and theory is emphasised throughout the course.

All students are initially registered on the MSc Applied Statistics. After a common first year of core modules in theoretical and applied statistics, the second year allows you to orient your programme of studies towards your own particular interests and career objectives. You select 4 modules (each running over a single term) from a range of specialist streams.

In addition to undertaking your 4 chosen option modules, you also complete a project - a sustained, independent investigation into a subject that interests you.

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While practically orientated, this postgraduate degree in applied statistics and financial modelling proceeds from a strong theoretical background so as to develop your ability to tackle new and non-standard problems with confidence. The mutual dependence of practice and theory is emphasised wherever possible.

The programme is ideal if you are considering a career move into statistics, or if your work already involves aspects of data collection and exploration, the interpretation of statistics, or the use of advanced stochastic modelling techniques in the area of quantitative finance.

The programme has been specially designed to meet the personal and career development needs of people who want to continue working while also studying in the evening. Many of our students, as part of their everyday work, are involved in data analysis, the interpretation of statistics, the optimal design and control of systems, and the modelling and prediction of time-dependent phenomena. They bring a wealth of knowledge and experience into the classroom, and you’ll find yourself surrounded by committed, enthusiastic students from all backgrounds, careers and cultures.

Why study this course at Birkbeck?

Covers both theory and application of stochastic and statistical modelling techniques required to solve applied problems in industry, the public services, scientific research and commerce.
Accredited by the Royal Statistical Society - graduates are normally granted Graduate Statistician (GradStat) status.
Birkbeck brings together research and teaching across economics and finance, mathematics and statistics in a single department, which creates significant interdisciplinary synergies.
Our teaching is informed by the needs of employers and you will be taught by academics who are professional practitioners involved in the world of economics and international finance. They provide specialist advice and in-house training for government departments, City firms and banks.
Our Department houses 5 research groups, in Applied Mathematics and Finance, Econometrics and Statistical Science, Macroeconomics, Microeconomics, and Pure Mathematics, which host visiting speakers and organise seminars. The Birkbeck Centre for Applied Macroeconomics and the Commodities Finance Centre are our 2 research centres, which disseminate research, host events and house visiting academics.
You will have access to a wide range of study resources, including University of London seminar programmes in probability and statistics, and excellent library facilities close by in Bloomsbury. Extensive computing facilities include PCs and UNIX platforms.

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This Masters in Environmental Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.

Why this programme

• The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
• Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
• Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
• You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
• You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
• You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
• Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)

• Bayesian statistics 
• Data analysis 
• Environmental statistics 
• Generalised linear models 
• Introduction to R programming
• Principles of GIS (10)
• Probability 1
• Regression models 
• Spatial statistics 
• Statistical inference 1
• Time series 
• Topographic mapping and landscape monitoring
• Statistics project and dissertation.

1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting course is subject to approval by the Programme Director.

Summer (May – August)

Statistics project and dissertation (60) - applying statistical methods and modelling to data collected from research in environmental science, assessed by a dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.

Graduates of this programme have gone on to positions such as:

Research Officer Medical Statistics at Kenya Medical Research Institute (KEMRI) Welcome Trust.

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The PGDip/MSc in Applied Statistics and Datamining is a one-year taught programme run by the School of Mathematics and Statistics. The course is aimed at those with a good degree containing quantitative elements who wish to gain statistical data analysis skills.

Highlights

• The course is commercially relevant and has content aligned with the requirements in the commercial analysis sector. Dissertation topics are generated in part by commercial partners.
• Teaching includes widespread commercial software packages (SAS, SPSS) along with popular open-source tools (R).

Teaching format

The programme consists of two semesters with taught components which include a mixture of short, intensive courses with a large proportion of continuous assessment and more traditional lecture courses with end-of-semester exams.

For those on the MSc, the taught component will be followed by a 15,000-word dissertation project taking place during the last three months of the course.

The School of Mathematics and Statistics is well equipped with personal computers and laptops, a parallel computer and an on-site library.

Further particulars regarding curriculum development.

Modules

The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2017-2018 academic year; some elements may be subject to change for 2018 entry.

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Introduction

This course provides an understanding of social research, with a particular focus on social statistics and quantitative methods. The course includes orientation material on social research methods as a whole, and detailed training on a wide range of statistical methods, with advanced modules on data management and emerging priority research areas, such as big data and social network analysis.
Teaching covers the theories behind the methods, and the practical work in using datasets and analysing them with statistical software. Students will gain a variety of highly marketable skills in the areas of social research and social statistics.

Key information

- Degree type: MSc, Postgraduate Diploma
- Study methods: Full-time, Part-time
- Start date: Full-time: SeptemberPart-time: September/JanuarySee semester dates
- Course Director: Dave Griffiths
- Location: Stirling Campus

Course objectives

This course provides an understanding of social research, with a particular focus on social statistics and quantitative methods. The course includes orientation material on social research methods as a whole, and detailed training on a wide range of statistical methods, with advanced modules on data management and emerging priority research areas, such as big data and social network analysis.
Teaching covers the theories behind the methods, and the practical work in using datasets and analysing them with statistical software. Students will gain a variety of highly marketable skills in the areas of social research and social statistics.

English language requirements

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.5 with 6.0 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade B
- Pearson Test of English (Academic): 60 with 56 in each component
- IBT TOEFL: 90 with no subtest less than 20

For more information go to http://www.stir.ac.uk/study-in-the-uk/entry-requirements/english/

If you don’t meet the required score you may be able to register for one of our pre-sessional English courses. To register you must hold a conditional offer for your course and have an IELTS score 0.5 or 1.0 below the required standard.

If you don’t meet the required score you may be able to register for one of our pre-sessional English courses. To register you must hold a conditional offer for your course and have an IELTS score 0.5 or 1.0 below the required standard. View the range of pre-sessional courses http://www.intohigher.com/uk/en-gb/our-centres/into-university-of-stirling/studying/our-courses/course-list/pre-sessional-english.aspx .

Structure and content

Students will undertake four core modules, two option modules and complete a 15,000 word dissertation. In the full time programme, 3 modules are completed during the Autumn semester, 3 in the Spring, and the dissertation submitted in the summer. Module either cover wider topics in social research, or focus on understanding and implementing advanced quantitative methods.

Core modules

- Research Design and Process
- Quantitative Data Analysis
- Advanced Data Analysis
- Advanced Data Management
- Using Big Data in Social Research

Option modules
Students will also select two option modules from a range of applied social research topics. The recommended option is Social Network Analysis.

Other options include The Nature of Social Enquiry, Policy Analysis and Evaluation Research, Qualitative Analysis and Research Methods in Criminology and Socio-Legal Studies. Some of these modules will be particularly suitable for students with an interest in mixed methods research.

Delivery and assessment

Modules are generally a combination of lectures and workshops. Teaching largely takes place on Tuesdays, although some components might take place on other days. The contact hours are sympathetic to those working alongside their studies. Most teaching is performed in smaller classes, with group activities. Modules are usually assessed by an examination, software based assignments, and essays.

Why Stirling?

REF2014
In REF2014 Stirling was placed 6th in Scotland and 45th in the UK with almost three quarters of research activity rated either world-leading or internationally excellent.

Career opportunities

Social statistics are an important area within applied social research, offering employment opportunities within the private, public and voluntary sectors, as well as further study. Students will develop thorough knowledge of software and learn a range of sought-after technical skills, including accessing, preparing, analysing and summarising complex quantitative datasets. The course is also designed to provide the technical skill set required for further PhD study.

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Why this course?

This one year masters degree will provide vocational training in applied statistics. This is a conversion course, designed for candidates from a broad background of disciplines. Students will gain skills in:

• problem solving
• big data
• the use of statistical software for data analysis and reporting

What you’ll study

Semester 1:

The modules available in semester 1 will equip you with fundamental statistical and data analysis skills.

Semester 2:

Semester 2 provides a range of modules, each focusing on a different applied element of being a statistician/analyst. These are all optional, allowing you to tailor this course to suit your career interests.

Semester 3:

In semester 3 you'll undertake a research project in which you'll work on a real-life data set, putting the theoretical skills you have learned into practice.

Programme skills set

On the programme you'll have the opportunity to acquire:

• an in-depth knowledge of modern statistical methods used to analyse and visualise real-life data sets, and the experience of how to apply these methods in a professional setting
• skills in using statistical software packages used in government, industry and commerce
• the ability to interpret the output from statistical tests and data analyses, and communicate your findings to a variety of audiences including health professionals, scientists, government officials, managers and stakeholders who may have an interest in the problem
• problem solving and high numeracy skills widely sought after in the commercial sector
• practical experience of statistical consultancy and how to interact with professionals who require statistical analyses of their data

Facilities

The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and access to University computing laboratories, with all necessary software available.

You'll also have access to a common room facility which gives you a modern and flexible area for individual and group study work, and is also a relaxing social space.  

Careers

The MSc in Applied Statistics will provide graduates with skills in the statistical analysis of data from a wide range of disciplines. These skills are required by many employers in sectors such as:

• investment companies 
• financial institutions 
• pharmaceutical industry 
• medical research 
• government organisations 
• retailers 
• internet information providers such as Google or Bing

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Statistics facilitates vital decision-making where there would otherwise be uncertainty. Social policy, medical practice and engineering all rely substantially on statistics and their correct use and interpretation. In these instances, their impact can be life-saving.

Statisticians work in many fields, from government to market research, measuring anything from changes in the environment revealing the effects of global warming, to the effectiveness of medicines. There are a large number of employment opportunities for our graduates in medical statistics, medical research, commerce and industry, particularly the pharmaceutical industry; as well as career opportunities both in areas directly related to statistics, such as accountancy, and wider afield in areas like computing, environmental science and law.

Our practically-orientated course gives you the skills employers are looking for – not just in terms of statistical knowledge, but transferable skills which will be useful whatever field you decide to work in. There is a shortage of well-qualified statisticians across the scientific, industrial and public sectors and a great demand for data analysts and statistical consultants, which our course has been specifically designed to meet.

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Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

Our Department of Mathematical is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

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Postgraduate degree course in Mathematics, Operational Research, Statistics and Econometrics (MORSE) Masters/MSc:

This programme is both technical and pragmatic. You will acquire the ability to integrate state-of-the-art knowledge of statistics and optimisation to address, analyse and provide a rational appraisal of a given problem in different professional contexts. This is a multidisciplinary field that involves the study of mathematical optimisation techniques, operational research methods, programming and statistics with their applications to economics, finance, medicine, industrial management, natural sciences and others. The programme produces highly qualified students in statistics, operations research and econometrics with applications to economics and business management. The programme provides ideal preparation for a career in economics, health care, finance, banking, insurance, actuarial science, business management, governmental or academic institutions.

To be accepted onto this programme a high standard in a mathematically-based undergraduate degree must have been achieved, equivalent to a UK upper second or first class degree.

Course details

In the recent years, mathematical optimization and statistics have experienced significant new developments. With these developments, the system engineering, information science, signal and image processing, statistical error correction and cryptography are being revolutionised.

This has created urgent need, in both academic research and in practical implementation, for a new generation of mathematicians trained to work at the frontiers of mathematical optimization, statistics and their applications to engineering, healthcare, finance and economics.

Researchers at the University of Birmingham have recently shown how the modern optimization and statistical methods are successfully applied to engineering design, financial and economical data analysis, meta-analysis, economic equilibrium, network communication, and combinatorial optimization.

Related links 

• Postgraduate degree courses, School of Mathematics

Learning and teaching

In the Autumn and Spring semesters, you will take masters-level courses in both advanced theory and applications of operational research, optimization and statistics, as well as the courses in modern computational techniques and data analysis.

In the summer you will undertake a research project, working with research leaders in optimization, statistics and econometrics, alongside mathematics and computation. These courses and project will provide relevant training in quantitative analysis together with multidisciplinary research and communication, a transferable skill, for whichever career path the MSc (MORSE) leads you to. 

Employability

Career opportunities

The course modules and research project will provide you with essential training in quantitative analysis together with multidisciplinary research and communication, a transferable skill which you will find valuable whatever career path you

pursue. Our graduates benefit from a growing global demand for these skills in sectors including economics, medicine, finance, insurance and industrial management.

University Careers Network

Preparation for your career should be one of the first things you think about as you start university. Whether you have a clear idea of where your future aspirations lie or want to consider the broad range of opportunities available once you have a Birmingham degree, our Careers Network can help you achieve your goal.

Our unique careers guidance service is tailored to your academic subject area, offering a specialised team (in each of the five academic colleges) who can give you expert advice. Our team source exclusive work experience opportunities to help you stand out amongst the competition, with mentoring, global internships and placements available to you. Once you have a career in your sights, one-to-one support with CVs and job applications will help give you the edge.

If you make the most of the wide range of services you will be able to develop your career from the moment you arrive.

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This programme will help you develop professionally in the theory and practice of statistics and operational research (OR), providing the foundations for a successful career.

This programme will prepare you for work in areas such as the medical and health industry, government, the financial sector and any other area where modern statistical tools and OR techniques are used. You will also develop the wider skills required for solving problems, working in teams and time management.

You will be able to identify appropriate statistical or operational techniques, which can be applied to practical problems, and will acquire extensive skills in modelling using the packages R for Statistics and Arena for simulation.

Programme structure

This MSc consists of lecture-based courses and practical, lab-based courses. You will be assessed by exams, written reports, programming assignments and a dissertation project. The set of courses available is subject to review in order to maintain a modern and relevant MSc programme.

Previous compulsory courses for 2017-18:

• Bayesian Theory
• Fundamentals of Operational Research
• Fundamentals of Optimization
• Generalised Regression Models
• Methodology, Modelling and Consulting Skills
• Simulation
• Statistical Programming
• Statistical Research Skills

Previous optional courses for 2017-18 include:

• The Analysis of Survival Data
• Bayesian Data Analysis
• Biomedical Data Science
• Credit Scoring
• Genetic Epidemiology
• Incomplete Data Analysis
• Integer and Combinatorial Optimization
• Large Scale Optimization for Data Science
• Machine Learning Practical
• Nonparametric Regression Models
• Operational Research in the Energy Industry
• Python Programming
• Risk and Logistics
• Scientific Computing
• Statistical Consultancy
• Stochastic Modelling
• Time Series
• Topics in Applied Operational Research
• Topics in Applied Optimization

Career opportunities

This programme is ideal for students who wish to apply their statistics and operational research knowledge within a wide range of sectors including the medical and health sector, government and finance. The advanced problem-solving skills you will develop will be highly prized by many employers.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

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Actuaries evaluate and manage financial risk. They make financial sense of the future for their clients by applying advanced mathematical and statistical techniques to solve complex financial problems.

Qualifying as an actuary is a passport to a wide variety of careers in insurance companies, investments, pensions, health care and banking – not just in the UK, but throughout the world. Kent is one of a very few universities in the UK to teach the subject.

Our MSc in Applied Actuarial Science is fully accredited by the Institute and Faculty of Actuaries; it also provides a fast-track route to qualifying as an actuary, because students who achieve a high enough overall mark in this programme can obtain exemptions from the professional examinations included within their studies.

The MSc is available as a full-time (one-year) or part-time (two-year) programme and is suitable for those who have completed a first degree or postgraduate diploma in Actuarial Science, or those who have studied the majority of the earlier subjects in the Core Technical Stage subjects.

Visit the website https://www.kent.ac.uk/courses/postgraduate/174/applied-actuarial-science

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills.

In 2010, the Centre for Actuarial Science, Risk and Investment (CASRI) was set up within SMSAS to reflect the widening scope of the teaching and research of the staff. Areas of research interest include economic capital and risk management for financial services firms, mortality and longevity modelling, longevity indices and markets. Other research topics include genetics and insurance, insurance economics, pensions and corporate reporting.

The Centre includes 13 professionally qualified actuaries with many years’ practical experience in insurance and pensions, and who maintain excellent links with the actuarial profession.

Course structure

The course is based on a ‘core modules plus options’ structure and exemptions can be gained from the following professional examinations in the Core Applications Stage and Specialist Technical Stage: CA1, CA3, ST2, ST4 to ST9. You can also choose the optional Financial Modelling modules, which prepare you for subject CA2 in the Core Applications Stage. Find out more about accreditation for this programme (http://www.kent.ac.uk/casri/Accreditation/index.html) and the Institute and Faculty of Actuaries examinations (http://www.actuaries.org.uk/students/pages/our-exams-explained).

You must take 180 credits in order to pass the MSc. If you take fewer than 180 credits, you may be eligible for the Postgraduate Diploma in Applied Actuarial Science.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

MA909 - Enterprise Risk Management (30 credits)
MA912 - Life Insurance (30 credits)
MA914 - Pensions and Other Benefits (30 credits)
MA915 - Finance and Investment (30 credits)
MA916 - Derivative Securities (30 credits)
MA917 - General Insurance - Reserving and Capital Modelling (30 credits)
MA918 - General Insurance - Premium Rating (30 credits)
MA950 - Prophet (15 credits)
MA951 - Prophet 2 (15 credits)
MA952 - Financial Modelling (15 credits)
MA953 - Communications (15 credits)
MA921 - Actuarial Risk Management 1 (30 credits)
MA922 - Actuarial Risk Management 2 (30 credits)

Assessment

Assessment is usually by a mixture of coursework and examination; exact weightings vary from module to module.

- Accreditation
Students who are considered to have performed sufficiently well in the programme (both in examinations and coursework), as determined by an examiner appointed by the UK Actuarial Profession, will be exempt from subjects CA1, CA3 and the Specialist Technical subjects studied within the programme.

If you fail to achieve a suitable overall standard, you might still be awarded individual module exemptions as recommended by the Profession’s examiner. Please note that individual exemptions are granted based on the final written examinations only.

Programme aims

This programme aims to:

- provide successful students with eligibility for subject exemptions from the Core Application and Specialist Technical series of examinations of the Institute and Faculty of Actuaries. This means obtaining a thorough knowledge of core actuarial applications, developing the ability to apply this knowledge in a practical situation and gaining current knowledge and understanding of the practice of major areas in which actuaries are involved.

- develop your understanding, knowledge and awareness of current problems, much of which is at the forefront of current professional practice.

- ensure you are competent in the use of information technology, and are familiar with computers, together with the relevant software.

Careers

The UK Actuarial Profession

The UK Actuarial Profession is small, but influential and well rewarded. There are more than 6,500 actuaries currently employed in the UK, the majority of whom work in insurance companies and consultancy practices.

Survey results published by the Institute and Faculty of Actuaries (http://www.actuaries.org.uk/becoming-actuary/pages/what-can-actuary-earn) suggest that the average basic salary for a student actuary is £36,842 with pay and bonuses increasingly sharply as you become more experienced. The average basic salary of a Chief Actuary is £209,292.

As an actuary, your work is extremely varied and can include: advising companies on the amount of funds to set aside for employee pension payments; designing new insurance policies and setting premium rates; pricing financial derivatives and working in fund management and quantitative investment research; advising life insurance companies on he distribution of surplus funds; and estimating the effects of possible major disasters, such as earthquakes or hurricanes, and setting premium rates for insurance against such disasters. For more information about the actuarial profession, see http://www.actuaries.org.uk

- Employability support

Helping our students to develop strong employability skills is a key objective within the School and the University. We provide a wide range of services and support to equip you with transferable vocational skills that enable you to secure appropriate professional positions within industry. Within the School we run specialist seminars and provide advice on creating a strong CV, making job applications and successfully attending interviews and assessment centres.

Our graduates have gone on to successful careers in the actuarial, finance, insurance and risk sectors.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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