Masters Degrees in Medical Statistics, United Kingdom

The MSc in Medical Statistics combines in-depth training in mainstream advanced statistical modelling with a specialisation in medical applications.

This flexible degree programme allows you to blend theoretical and applied statistical disciplines, ideal for training in medical statistics. It combines compulsory and optional modules allowing you to train in a range of statistical techniques (and transferable skills) suitable for either careers in medical statistics and research-related professions, or for further academic research.

Options within the course vary from mainstream topics in statistical methodology to more specialised areas such as epidemiology and biostatistics.

You can also study this programme part time over 24 months.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Accreditation

Accreditation from the Royal Statistical Society is pending.

Course content

The first two semesters of your course will consist of taught modules, and in the third semester you’ll devote your time to a major dissertation in statistics or a research project in applied epidemiology and biostatistics. Within each semester you have the opportunity to choose from a range of optional modules, allowing you to specialise in the area of study of most interest to you.

You’ll be taught by experts from the School of Mathematics, The Centre for Epidemiology and Biostatistics, and The Clinical Trials Research Unit at Leeds, each bringing a different perspective to the subject of medical statistics.

You’ll be supervised for both your taught modules and your research project by professionals across the teaching units and you will be given the opportunity to utilise existing links with individual clinicians and medical research groups in the University of Leeds, Leeds NHS trust, and the Department of Health’s Information Centre in Leeds.

Throughout the course you’ll learn about new developments in statistics and be provided with the opportunity to undertake data analysis for a wide variety of statistical problems. You’ll build an appreciation of theoretical and practical perspectives on issues in medical statistics, whilst developing the ability to select and apply appropriate statistical methods for the analysis of medical data using suitably chosen software packages.

Course structure

Compulsory modules

• Introduction to Clinical Trials 15 credits
• Core Epidemiology 15 credits
• Introduction to Modelling 15 credits
• Statistical Computing 15 credits

Optional modules

• Research Project 60 credits
• Multilevel and Latent variable Modelling 15 credits
• Professional Spine 15 credits
• Independent Learning Skills in Epidemiology and Biostatistics 15 credits
• Advanced Modelling Strategies 15 credits
• Advanced Epidemiological Techniques 15 credits
• Linear Regression and Robustness 15 credits
• Statistical Theory 15 credits
• Multivariate Analysis 10 credits
• Time Series 10 credits
• Bayesian Statistics 10 credits
• Generalised Linear Models 10 credits
• Introduction to Statistics and DNA 10 credits
• Linear Regression and Robustness and Smoothing 20 credits
• Multivariate and Cluster Analysis 15 credits
• Time Series and Spectral Analysis 15 credits
• Bayesian Statistics and Causality 15 credits
• Generalised Linear and Additive Models 15 credits
• Independent Learning and Skills Project 15 credits
• Dissertation in Statistics 60 credits
• Statistics and DNA 15 credits

For more information on typical modules, read Medical Statistics MSc in the course catalogue

Learning and teaching

This course is taught by experts from the School of Mathematics, the Centre for Epidemiology and Biostatistics, and the Clinical Trials Research Unit at Leeds. You’ll study a mixture of modules taught by specialists in each area depending on your chosen optional modules. Teaching is done through a combination of lectures, small group workshops and a small number of practical exercises.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The project is assessed by a written dissertation and a short oral presentation.

Career opportunities

There is a shortage of well-qualified statisticians in the UK and other countries. Numeracy, in general, is an attribute keenly sought after by employers.

The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of professions - actuarial, betting and gaming industries, charitable organizations, commercial, environmental, financial, forensic and police investigation, government, market research, medical and pharmaceutical organisations. The course is designed specifically to meet this demand.

As a graduate of medical statistics you will have specialist knowledge that will help you progress your career into areas such as medical or epidemiological research. There are several aims to medical research, all of which involve a significant amount of statistics, monitoring and surveillance of health and disease, establishing causes of disease or factors associated with death or disease, detecting disease, preventing death or disease and evaluating treatments for disease. Medical statisticians looking to follow a career in medical research are mainly employed by pharmaceutical companies, university medical schools, research units and the NHS.

A medical statistician could also go into consultancy giving advice to researchers looking to set up clinical trials and needing their project to be assessed before funding is granted.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

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International Master's in Statistics - MSc: https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics

Overview

The International Master’s in Statistics develops your practical, statistical and computing skills to prepare you for a professional career in statistics or as a solid basis for further research in the area.

The programme has been designed to provide a deep understanding of the modern statistical methods required to model and analyse data. You will benefit from a thorough grounding in the ideas underlying these methods and develop your skills in key areas such as practical data analysis and data modelling.

It has been accredited by the Royal Statistical Society (RSS) and equips aspiring professional statisticians with the skills they need for posts in industry, government, research and teaching. It also enables you to develop a range of transferable skills that are attractive to employers within the public and private sectors.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics.

International Master's in Statistics with Finance - MSc: https://www.kent.ac.uk/courses/postgraduate/164/international-masters-statistics-finance

Overview

This programme, accredited by the Royal Statistical Society (RSS), equips aspiring professional statisticians with the skills they will need for posts in industry, government, research and teaching. It is suitable preparation too for careers in other fields requiring a strong statistical background.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics with Finance.

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. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Research areas

Biometry and ecological statistics
Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

Bayesian statistics
Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.
Bioinformatics, statistical genetics and medical statistics
Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

Nonparametric statistics
Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Professional recognition

The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status.

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

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Medical statistics is a fundamental scientific component of health research. Medical statisticians interact with biomedical researchers, epidemiologists and public health professionals and contribute to the effective translation of scientific research into patient benefits and clinical decision-making. As new biomedical problems emerge, there are exciting challenges in the application of existing tools and the development of new superior models.

Degree information

The UCL Medical Statistics degree provides students with a sound background in theoretical statistics as well as practical hands-on experience in designing, analysing and interpreting health studies, including trials and observational studies. The taught component equips students with analytical tools for health care economic evaluation, and the research project provides experience in using real clinical datasets.

Students undertake modules to the value of 180 credits.

The programme consists of a foundation course, six core modules (90 credits) two optional modules (30 credits) and the research dissertation (60 credits).

Core modules
-Foundation Course (not credit bearing)
-Statistical Inference
-Statistical Models and Data Analysis
-Medical Statistics I
-Medical Statistics II
-Statistical Computing
-Applied Bayesian Methods

Optional modules - at least one from:
-Statistics for Interpreting Genetic Data
-Bayesian Methods in Health Economics

and at least one from:
-Epidemiology
-Statistical Design of Investigations

Dissertation/report
All MSc students undertake an individual research project, culminating in a dissertation of approximately 10,000–12,000 words.

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

Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics, for example, the presentation of statistical graphs and tables.

Careers

Medical statisticians enable the application of the best possible quantitative methods in health research and assist in the reliable translation of research findings to public and patients’ health care.

The National Institute of Health Research (NIHR) has identified Medical Statistics as one of the priority areas in their capacity building strategy and has awarded UCL two studentships annually for this MSc.

Top career destinations for this degree:
-Graduate Bio-Statistician, PRA International
-Statistical and Epidemiological Modeller, University of Oxford
-Biostatistician, Boehringer Ingelheim
-PhD Statistical Science, University College London (UCL)

Employability
There is an acute shortage of medical statisticians in the UK and employment opportunities are excellent. Recent graduates from this programme have been employed by clinical trials units, pharmaceutical industry, NHS trusts and Universities (e.g. London School of Hygiene and Tropical Medicine, UCL).

Why study this degree at UCL?

One of the strengths of UCL Statistical Science is the breadth of expertise on offer; the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science.

UCL is linked with four NHS hospital trusts and hosts three biomedical research centres, four clinical trial units and an Institute of Clinical Trials and Methodology. Established links between the Department of Statistical Science, the NIHR UCLH/UCL Biomedical Research Centre and the Clinical Trial Units provide high-quality biomedical projects for Master's students and opportunities for excellent postgraduate teaching and medical research.

The programme has been accredited by the Royal Statistical Society. Graduates will automatically be granted the society's Graduate Statistician status on application.

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This is a part-time, modular based programme for health professionals who wish to strengthen their statistical skills and ability to analyse data.

Students will gain the confidence in carrying out the methods that are widely used in medical statistics, and interpreting the results for the practice of evidence-based health care. The flexible modular structure has been devised for busy professionals and to fit with the structure of specialist training. The regulations allow students to take up to four years to complete the MSc.

This is a joint programme between the Nuffield Department of Primary Care Health Sciences and the Department for Continuing Education's Continuing Professional Development Centre. The Programme works in collaboration with the renowned Centre for Evidence-Based Medicine in Oxford.

This course is designed for doctors, nurses, pharmacists, midwives and other healthcare professionals, seeking to consolidate their understanding and ability in medical statistics. Core modules introduce the students to methods for observational and clinical trials research. Optional modules offer the students skills in growth areas such as systematic review, meta-analysis, and big data epidemiology, or specialist areas such as statistical computing, diagnosis and screening research and others. Teaching is tailored to non-statisticians and delivered by an experienced team of tutors from University of Oxford who bridge the disciplines of medical statistics and evidence-based health care.

This programme guides students through core and optional modules and a dissertation to a qualification in the application of medical statistics to evidence-based health care. Compared to the main EBHC programme, this will suit those with basic statistical understanding who seek training who now seek deeper understanding on a broader base of statistical methods.

Visit the website https://www.conted.ox.ac.uk/about/msc-in-ebhc-medical-statistics

Course aims

The course aims to give healthcare professionals high competence in the concepts, methods, terminology and interpretation of medical statistics; and hence, enhance their ability to carry out their own research and to interpret published evidence.

• Gain competence in execution and interpretation of core statistical techniques used by medical statisticians (outside the context of clinical trials), particularly those used in multivariable analyses: multiple linear regression, logistic regression, and survival modelling; statistical analysis plans and statistical reporting.
• Gain competence in execution and interpretation of core statistical techniques used by medical statisticians in clinical trials.
• Gain competence in execution and interpretation of four other areas, selected by the student from the following options: meta-analysis; systematic review; big data epidemiology; statistical computing; diagnosis and screening; study design and research methods.
• Gain hands-on experience, supervised by a senior member of our medical statistics team, of the analysis or meta-analysis of healthcare data, in order to address a question in evidence-based health care.

Programme details

The MSc in EBHC Medical Statistics is a part-time course.

There are two compulsory modules, four option modules (two from group 1 and two more either from either group 1 or 2) and a dissertation.

Compulsory Modules

• Essential Medical Statistics
• Statistics for Clinical Trials

Optional Modules – 1

• Meta-analysis
• Big Data Epidemiology
• Statistical Computing with R and Stata (online)

Optional Modules – 2

• Introduction to Study Design and Research Methods
• Systematic Reviews
• Evidence-based Diagnosis and Screening

A module is run over an eight-week cycle where the first week is spent working on introductory activities using a Virtual Learning Environment, the second week is spent in Oxford for the face-to-face teaching week, there are then four post-Oxford activities (delivered through the VLE) which are designed to help you write your assignment. You then have a week of personal study and you will be required to submit your assignment electronically the following week.

Online modules are delivered entirely through a Virtual Learning Environment with the first week allocated to introductory activities. There are ten units to work through which are released week-by-week, you then have five weeks of personal study with use of a revision forum and then you will be required to submit your assignment electronically the following week.

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The course trains students from a variety of academic backgrounds to work as statisticians in various sectors including higher education, research institutions, the pharmaceutical industry, central government and national health services. It provides training in the theory and practice of statistics with special reference to clinical trials, epidemiology and clinical or laboratory research.

The PSI Andrew Hewett Prize is founded in memory of Andrew Hewett, an alumnus of the School and awarded by the PSI (Statisticians in the Pharmaceutical Industry) to the best student on the course.
Duration: one year full-time or part-time over two years. Modes of study explained.

- Full programme specification (pdf) (http://www.lshtm.ac.uk/edu/qualityassurance/ms_progspec.pdf)

Visit the website http://www.lshtm.ac.uk/study/masters/msms.html

For the MSc Medical Statistics it is preferred that students should normally have obtained a mathematically-based first degree which includes some statistics. Graduates from other fields who have quantitative skills and some familiarity with statistical ideas may also apply.

Any student who does not meet the minimum entry requirement above but who has relevant professional experience may still be eligible for admission. Qualifications and experience will be assessed from the application.

Intercalating this course

(http://www.lshtm.ac.uk/study/intercalate)

Undergraduate medical students can take a year out either to pursue related studies or work. The School welcomes applications from medical students wishing to intercalate after their third year of study from any recognised university in the world.

Why intercalate with us?:
Reputation: The School has an outstanding international reputation in public health & tropical medicine and is at the forefront of global health research. It is highly rated in a number of world rankings including:

- World’s leading research-focused graduate school (Times Higher Education World Rankings, 2013)
- Third in the world for social science and public health (US News Best Global Universities Ranking, 2014)
- Second in UK for research impact (Research Exercise Framework 2014)
- Top in Europe for impact (Leiden Ranking, 2015)

Highly recognised qualification: possessing a Master's from the School will give you a focused understanding of health and disease, broaden your career prospects and allow you to be immersed in research in a field of your choice.

Valuable skills: you will undertake an independent research project (summer project) in your chosen topic, equipping you with research skills that will distinguish you in a clinical environment. While your medical qualification will give you a breadth of knowledge; undertaking an intercalated degree will allow you to explore your main area of interest in greater depth.

Alumni network: the School has a strong international and diverse alumni community, with more than 20,000 alumni in over 180 countries.

MSc vs. BSc: undertaking an MSc is an excellent opportunity to develop in-depth specialist knowledge in your chosen topic and enhance your skills in scientific research. Postgraduate qualifications are increasingly sought after by clinicians and possessing a Masters qualification can assist you in your future career progression.

Objectives

By the end of this course students should be able to:

- select appropriate study designs to address questions of medical relevance

- select and apply appropriate statistical techniques for managing common types of medical data

- use various software packages for statistical analysis and data management

- interpret the results of statistical analyses and critically evaluate the use of statistics in the medical literature

- communicate effectively with statisticians and the wider medical community, in writing and orally through presentation of results of statistical analyses

- explore current and anticipated developments in medical statistics

Structure

Term 1:
All students take five compulsory modules:
- Foundations of Medical Statistics
- Introduction to Statistical Computing (Stata/SAS/R)
- Clinical Trials
- Basic Epidemiology
- Robust Statistical Methods

Terms 2 and 3:
Students take a total of five modules, one from each timetable slot (Slot 1, Slot 2 etc.). The list below shows recommended modules. There are other modules which can only be taken after consultation with the course director.

*Recommended modules

- Slot 1:
Generalised Linear Models (compulsory)

- Slot 2:
Statistical Methods in Epidemiology (compulsory)

- Slot 3:
Analysis of Hierarchical & Other Dependent Data*
Epidemiology of Non-Communicable Diseases
Modelling & the Dynamics of Infectious Diseases
Social Epidemiology

- Slot 4:
Survival Analysis and Bayesian Statistics (compulsory)

- Slot 5:
Advanced Statistical Modelling*
Advanced Statistical Methods in Epidemiology*

Further details for the course modules - http://www.lshtm.ac.uk/study/currentstudents/studentinformation/msc_module_handbook/section2_coursedescriptions/tmst.html

Project Report

During the summer months (July - August), students complete a research project, for submission by early September. This usually consists of analysing a set of data and writing a report, but methodological research can also be undertaken.

Find out how to apply here - http://www.lshtm.ac.uk/study/masters/msms.html#sixth

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These programmes offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS).

Research interests are diverse and include: Bayesian statistics; bioinformatics; biometry; ecological statistics; epidemic modelling; medical statistics; nonparametric statistics and semi-parametric modelling; risk and queueing theory; shape statistics.

Visit the website https://www.kent.ac.uk/courses/postgraduate/169/statistics

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. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Course structure

The research interests of the group are in line with the mainstream of statistics, with emphasis on both theoretical and applied subjects.

There are strong connections with a number of prestigious research universities such as Texas A&M University, the University of Texas, the University of Otago, the University of Sydney and other research institutions at home and abroad.

The group regularly receives research grants. The EPSRC has awarded two major grants, which support the National Centre for Statistical Ecology (NCSE), a joint venture between several institutions. A BBSRC grant supports stochastic modelling in bioscience.

Research areas

- Biometry and ecological statistics

Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

- Bayesian statistics

Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.

- Bioinformatics, statistical genetics and medical statistics

Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

- Nonparametric statistics

Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

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

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The MSc in Medical Statistics at the University of Leicester is a well-established and successful course based in the Biostatistics and Genetic Epidemiology research groups in the Medical School of the University of Leicester. This course is accredited by the Royal Statistical Society. On graduation you will be able to apply for the professional award of Graduate Statistician.

The orientation of the course is applied and vocational; it aims to produce graduates who can immediately work as medical statisticians in pharmaceutical companies, research units and the NHS.

While all necessary theory is covered, the emphasis throughout is on applying and adapting it to real-life circumstances. The central role of IT in implementing modern statistics is constantly emphasised. Students will use statistical software Stata, R, WinBUGS, MLwiN and SAS in a course dedicated computer lab.

The Core Modules

Fundamentals of Medical Statistics, Statistical Modelling, Computational Intensive Methods, Advanced Statistical Modelling, Clinical Trials and Epidemiology.
Choose one optional module from Further Topics in Medical Statistics, Genetic Epidemiology and Health Technology Assessment.
Plus a Research Project during the final 12 weeks of the course
Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.

Modules are taught in week long blocks.

Course aims

The aim of the course is to produce graduates who can immediately work as medical/bio statisticians in pharmaceutical companies, university medical schools, research units and the NHS.

Funding

We have studentships available for 2017 entry, these cover UK/EU fees and may provide living expenses, please contact the Admissions Tutor for details. Eligibility criteria apply.

Key facts for this course are available at http://www2.le.ac.uk/departments/health-sciences/PG/pgt

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About the course

This new course is run in conjunction with the Medical Statistics Group in the University’s School of Health and Related Research (ScHARR). Accredited by the Royal Statistical Society, it provides professional training for a career in the medical, pharmaceutical and health services industries. The course is based on the MSc Statistics with additional training in specialist areas of medical applications.

Your career

Our graduates go into finance, manufacturing and pharmaceuticals. They work for government agencies and research institutes with major organisations such as First Direct, GlaxoSmithKline, Marks and Spencer, the Government Statistical Service and Medical Research Council units. Our courses can also prepare you for PhD-level research.

About us

Our academics are in demand. They are members of international societies and organisations, and they speak at conferences around the world. They bring new ideas into the classroom so you can see how research is improving on existing approaches. Our solar scientists were the first to record musical sounds created by vibrations in the sun’s atmosphere.

Our Statistical Services Unit works with industry, commerce and the public sector. The services they provide include consultancy, training courses and computer software development.

Different ways to study

You can study full-time over a year or part-time over two to three years via online distance learning. The MSc Mathematics is only available as a full-time course.

Studentships

You may be able to get funding from the University or an external company. Course-specific studentships may also be available. You should apply for these as soon as possible.

Core modules

Data Analysis; Statistical Laboratory; Linear Models; Epidemiological Methods and Time Series; Bayesian Inference and Further Clinical Trials; Sampling, Design and Medical Statistics.

Teaching and assessment

There are lectures, tutorials and computing sessions. You’ll do group work, presentations and role play. Most statistics lectures are recorded so you can watch them again later.

The distance learning option is taught online with support via email and phone. Distance learners also come to the University for residential weeks. You’re assessed by exams, project work and a dissertation.

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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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Overview

The MSc Statistics offers a modern advanced curriculum in statistics which will enable you to broaden and deepen your understanding of the subject and its applications.

The programme will provide you with specific techniques and skills suitable for a professional career in statistics or as a solid basis for research in the area.

Optional topics typically include generalised linear models, Markov Chain Monte Carlo, the bootstrap, multivariate analysis, spatial statistics, time series and forecasting, multilevel models, stochastic finance, and shape and image analysis.

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).

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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Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, law and marketing. New and exciting opportunities in industry, medicine, government, commerce or research await the graduate who has gained the quantitative skills training provided by this MSc.

Degree information

The programme uses a broad-based approach to statistics, providing up-to-date training in the major applications and an excellent balance between theory and application. It covers modern ideas in statistics including applied Bayesian methods, generalised linear modelling and object-oriented statistical computing, together with a grounding in traditional statistical theory and methods.

Students undertake modules to the value of 180 credits.

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

Core modules
-Foundation Course (not credit bearing)
-Statistical Models and Data Analysis
-Statistical Design of Investigations
-Statistical Computing
-Applied Bayesian Methods

Optional modules
-Decision and Risk
-Stochastic Systems
-Forecasting
-Statistical Inference
-Medical Statistics I
-Medical Statistics II
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Factorial Experimentation
-Selected Topics in Statistics
-Bayesian Methods in Health Economics
-Quantitative Modelling of Operational Risk and Insurance Analytics

Dissertation/report
All MSc students undertake an independent research project, culminating in a dissertation of approximately 10,000–12,000 words.

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

Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics e.g. the presentation of statistical graphs and tables.

Careers

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

Top career destinations for this degree:
-Management Associate, HSBC
-Statistical Analyst, Nielsen
-PhD Statistics, University College London (UCL)
-Mortgage Specialist, Citibank
-Research Assistant Statistician, Cambridge Institute of Public Health

Employability
The Statistics MSc provides skills that are currently highly sought after. Graduates receive advanced training in methods and computational tools for data analysis that companies and research organisations value. For instance, the new directives and laws for risk assessments in the banking and insurance industries, as well as the healthcare sector, require statistical experts trained at graduate level. The large amount of data processing in various industries (known as "data deluge") also necessitates cutting-edge knowledge in statistics. As a result, our recent graduates have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

One of the strengths of UCL Statistical Science is the breadth of expertise on offer; the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science.

London provides an excellent environment in which to study statistical science, being the home of the Royal Statistical Society as well as a base for a large community of statisticians, both academic and non-academic.

The Statistics MSc has been accredited by the Royal Statistical Society. Graduates will automatically be granted the society's Graduate Statistician status on application.

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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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This Masters in Biostatistics 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.

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
◾Biostatistics
◾Generalised linear models
◾Introduction to R programming
◾Probability 1
◾Regression models
◾Statistical inference 1
◾Statistics project and dissertation.

Optional courses (five chosen, but at least one course must be from Group 1)
Group 1
◾Data analysis
◾Professional skills.

Group 2
◾Data management and analytics using SAS
◾Design of experiments
◾Functional data analysis
◾Spatial statistics
◾Statistical genetics
◾Time series.

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 courses 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 a biomedical discipline, 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.

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Our MPhil/PhD degree in Mathematics and Statistics aims to train you to conduct research of a high academic standard and to make original contributions to the subject.

The programme involves coursework (where suitable) and research training, but its major component is the preparation of a substantial research thesis. The thesis should demonstrate a sound understanding of the main issues in the area and add to existing knowledge.

Research interests in mathematics and statistics include: mathematical finance, in particular the analysis of risk and numerical computation; mathematical physics and partial differential equations; approximation theory and numerical analysis; probability and stochastic processes, pure and applied; applied statistics and multivariate analysis; covariance modelling for repeated measures and longitudinal data; medical statistics; combinatorics, algebra and designs.

Our research

Birkbeck is one of the world’s leading research-intensive institutions. Our cutting-edge scholarship informs public policy, achieves scientific advances, supports the economy, promotes culture and the arts, and makes a positive difference to society.

Birkbeck’s research excellence was confirmed in the 2014 Research Excellence Framework, which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

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About the course

This course prepares you for a career as a statistician. You’ll learn how to solve practical statistical problems and develop personal skills including presentation and time management. This course is accredited by the Royal Statistical Society.

Your career

Our graduates go into finance, manufacturing and pharmaceuticals. They work for government agencies and research institutes with major organisations such as First Direct, GlaxoSmithKline, Marks and Spencer, the Government Statistical Service and Medical Research Council units. Our courses can also prepare you for PhD-level research.

About us

Our academics are in demand. They are members of international societies and organisations, and they speak at conferences around the world. They bring new ideas into the classroom so you can see how research is improving on existing approaches. Our solar scientists were the first to record musical sounds created by vibrations in the sun’s atmosphere.

Our Statistical Services Unit works with industry, commerce and the public sector. The services they provide include consultancy, training courses and computer software development.

Different ways to study

You can study full-time over a year or part-time over two to three years via online distance learning. The MSc Mathematics is only available as a full-time course.

Studentships

You may be able to get funding from the University or an external company. Course-specific studentships may also be available. You should apply for these as soon as possible.

Core modules

Data Analysis; Statistical Laboratory; Linear Models; Dependent Data; Inference; Sampling, Design and Medical Statistics.

Teaching and assessment

There are lectures, tutorials and computing sessions. You’ll do group work, presentations and role play. Most statistics lectures are recorded so you can watch them again later.

The distance learning option is taught online with support via email and phone. Distance learners also come to the University for residential weeks. You’re assessed by exams, project work and a dissertation.

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