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.
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:
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.
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.
Classes are delivered by a number of teaching methods:
Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.
The form of assessment varies for each class. For most classes the assessment involves both coursework and examinations.
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:
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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:
Previous optional courses for 2017-18 include:
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.
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.
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.
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 in 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).
At least two from a choice of Statistical Science modules including:
Up to two from a choice of Computer Science modules including:
All students undertake an independent research project, culminating in a dissertation usually of 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.
Further information on modules and degree structure is available on the department website: Data Science MSc
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:
Data science professionals are likely to be increasingly sought after as the integration of statistical and computational analytical tools becomes essential in all kinds of organisations and enterprises. A thorough 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 should be accompanied by statistical expertise at graduate level. Data scientists need a broad background knowledge so that they will be able to adapt 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.
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.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
The following REF score was awarded to the department: Statistical Science
82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.