Masters Degrees in Applied Statistics, United Kingdom

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 compulsory modules covered in Semester 1 will equip you with fundamental probability and data analysis skills. In Semester 2 there's four compulsory modules, each focusing on a different applied element of being a statistician. The course concludes with a research project which 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

Guest lectures
Several modules will be taught by academics who also work for other organisations including government and health services.

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.

Course content

Semester 1 Compulsory classes:
The three compulsory classes covered in semester 1 will equip you with fundamental probability and data analysis skills.

-Foundations of Probability & Statistics
-Data Analytics in R
-Applied Statistical Modelling

Semester 2 Compulsory classes:
Each class focuses on a different applied element of being a statistician.

-Medical Statistics
-Bayesian Spatial Statistics
-Effective Statistical Consultancy
-Risk Analysis
-Survey Design & Analysis
-Semester 3

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.

How can I fund my course?

A number of scholarships are available for outstanding UK, EU and international applicants. For details, please visit our scholarship search: https://www.strath.ac.uk/studywithus/scholarships/

Scottish students:
Students living in Scotland can find out more about funding from the Student Awards Agency Scotland.

English/EU students:
Students ordinarily resident in England may be eligible to apply for a loan of up to £10,000 to cover their tuition fees and living costs. Students resident in the EU may also apply.

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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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 50 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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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.

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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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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MSc in Applied Statistics and Datamining

• Aimed at individuals with a good degree containing quantitative elements, who wish to gain statistical data analysis skills relevant to business, commerce and other applications.

• Preparation for commercial data analysis.
• A commercially relevant programme of study that has content aligned with the requirements of partners in the commercial analysis sector.

• Strongly applied bias, with an emphasis on application in the commercial sector.

• Dissertation topics are generated in part by our commercial partners.

• Teaching includes widespread commercial software packages e.g. SAS, SPSS, along with popular open-source tools e.g. R.

• Teaching consists of a mixture of short, intense courses with a large proportion of continuous assessment and more traditional lecture courses with end of semester exams.

• A graduate from this programme would be seeking employment as an analyst within a company, research body, government, or as a statistical consultant.

Features

* Opportunities to work closely, and undertake project work, within a research group.

* Access to a wide range of advanced MMath courses across the entire spectrum of Mathematics and Statistics.

* The School is well equipped with personal computers and laptops, a parallel computer and an on-site library, and has attracted substantial amounts of external funding.

Careers

Our graduates hold positions at leading universities or companies in areas as diverse as business administration, computer science and modelling, fisheries laboratories and pure mathematics. In short, a postgraduate degree in mathematics or statistics from St Andrews opens the way for a variety of careers.
Our recent graduates at Masters and Doctoral level have, amongst other things:
• Moved on to postdoctoral studies.
• Joined the academic staff of leading UK and international universities.
• Found highly-paid positions in analysing futures/finance for large consulting firms and major financial institutions, for example: Scottish and Southern Energy, RBS, Capital One, Aquila Insight, Aviva, PwC, American Express, Goldman Sachs, Tesco Bank.
• Found rewarding and challenging positions in the computer industry.
• Found academically rewarding positions and careers in government agencies, including, for example, GCHQ.
• Joined government and non-governmental organisations to advise wildlife and conservation managers, including, for example, the Wildlife Conservation Society (WCS).
• Improved their mathematics qualifications, hence enhancing their positions and prospects in the secondary and tertiary education sectors.

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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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Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

Degree information

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules from computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

Core modules
-Introduction to Statistical Data Science
-Introduction to Supervised Learning
-Statistical Design of Investigations
-Statistical Computing

Optional modules - st least two from a choice of Statistical Science modules including:
-Applied Bayesian Methods
-Decision & Risk
-Factorial Experimentation
-Forecasting
-Quantitative Modelling of Operational Risk and Insurance Analytics
-Selected Topics in Statistics
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Stochastic Systems

Up to two from a choice of Computer Science modules including:
-Affective Computing and Human-Robot Interaction
-Graphical Models
-Statistical Natural Language Processing
-Information Retrieval & Data Mining

Dissertation/report
All students undertake an independent research project, culminating in a dissertation usually comprising 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Careers

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study.

The Data Science MSc is a new programme with the first cohort of students due to graduate in 2017. Recent career destinations for graduates of the related Statistics MSc include:
-Towers Watson, Actuary Analyst
-Proctor & Gamble, Statistician
-Ernst & Young, Audit Associate
-Collinson Group, Insurance Analyst
-UCL, PhD Statistical Science

Employability
Data science professionals will be highly sought after as the integration of statistical and computational analytical tools becomes increasingly essential in all kinds of organisations and enterprises. A solid understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should go along with statistical expertise as graduate level. Data scientists should have a broad background so that they will be able to adapt themselves to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

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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.

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.

About the School of Mathematics

The School of Mathematics is one of seven schools in the College of Engineering and Physical Sciences. The school is situated in the Watson Building on the main Edgbaston campus of the University of Birmingham. There are about 50 academic staff, 15 research staff, 10 support staff, 60 postgraduate students and 600 undergraduate students.
At the School of Mathematics we take the personal development and careers planning of our students very seriously. Jointly with the University of Birmingham's Careers Network we have developed a structured programme to support maths students with their career planning from when they arrive to when they graduate and beyond.

Funding and Scholarships

There are many ways to finance your postgraduate study at the University of Birmingham. To see what funding and scholarships are available, please visit: http://www.birmingham.ac.uk/postgraduate/funding

Open Days

Explore postgraduate study at Birmingham at our on-campus open days.
Register to attend at: http://www.birmingham.ac.uk/postgraduate/visit

Virtual Open Days

If you can’t make it to one of our on-campus open days, our virtual open days run regularly throughout the year. For more information, please visit: http://www.pg.bham.ac.uk

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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. In addition, you will acquire the ability to use high-level applications in Excel.

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 2016-17:

• Computing for Statistics
• Fundamentals of Operational Research
• Fundamentals of Optimization
• Likelihood and Generalised Linear Models
• Methodology, Modelling and Consulting Skills
• Simulation
• Statistical Regression Models
• Stochastic Modelling
• Statistical Theory or Bayesian Theory

Previous option courses for 2016-17 include:

• The Analysis of Survival Data
• Categorical Data Analysis
• Clinical Trials
• Computing for Operational Research and Finance
• Credit Scoring
• Data Analysis
• Genetic Epidemiology
• Large Scale Optimization for Data Science
• Machine Learning & Pattern Recognition
• Multivariate Data Analysis
• Nonparametric Regression
• Operational Research in the Airline Industry
• Operational Research in Telecommunications
• Risk Analysis
• Stochastic Models in Biology
• Stochastic Optimization
• Time Series Analysis and Forecasting

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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In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:

• classical and Bayesian ideologies
• linear and generalised linear models
• computational statistics applied to a range of models and applications
• regression
• data analysis

Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.

Programme structure

To be awarded the MSc degree you need to obtain a total of 180 credits. All students take courses during semester 1 and 2 to the value of 120 credits which will be a combination of compulsory and optional courses. Successful performance in these courses (assessed via coursework or examinations or both) permits you to start work on your dissertation (60 credits) for the award of the MSc degree. The dissertation will generally take the form of two consultancy-style case projects or an externally supervised project.

The set of courses available is subject to review in order to maintain a modern and relevant MSc programme.

Previous compulsory courses for 2016-17:

• Statistical Theory (10 credits, semester 1)
• Statistical Regression Models (10 credits, semester 1)
• Bayesian Theory (10 credits, semester 1)
• Statistical Programming (10 credits, semester 1)
• Bayesian Data Analysis (10 credits, semester 2)
• Likelihood and Generalised Linear Models (10 credits, semester 2)

Previous optional courses for 2016-17 include:

• Statistical Consultancy (10 credits, semester 1)
• Fundamentals of Optimization (10 credits, semester 1)
• The Analysis of Survival Data (10 credits, semester 2)
• Stochastic Modelling (10 credits, semester 2)
• Multilevel Modelling (20 credits, semester 2)
• Nonparametric regression (10 credits, semester 2)
• Large Scale Optimization for Data Science (10 credits, semester 2)
• Modern Optimization Methods for Big Data Problems (10 credits, semester 2)
• Time Series Analysis and Forecasting (5 credits, semester 2)
• Combinatorial Optimization (5 credits, semester 2)
• Probabilistic Modelling and Reasoning (10 credits, semester 2)

Learning outcomes

At the end of this programme you will have:

• knowledge and understanding of statistical theory and its applications within data science
• the ability to formulate suitable statistical models for new problems, fit these models to real data and correctly interpret the results
• the ability to assess the validity of statistical models and their associated limitations
• practical experience of implementing a range of computational techniques using statistical software R and BUGS/JAGS

Career opportunities

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science.

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