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Mathematics×

Masters Degrees in Mathematical statistics

We have 85 Masters Degrees in Mathematical statistics

Masters degrees in Mathematical Statistics are concerned primarily with the theories that form the basis of methods of probability and inference. They examine the application of these theories to the collection, analysis and description of data.

Related subjects include Applied Statistics and Computational Statistics. The main entry requirement is typically an undergraduate degree in a relevant Mathematics subject.

Why study a Masters in Mathematical Statistics?

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International Master's in Statistics - MSc. https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics. Read more
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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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). Read more
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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Statistics is one of the most important fields of study in the world. The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society. Read more
Statistics is one of the most important fields of study in the world. The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society. If you are a logical person and enjoy solving problems, statistics at Essex is for you.

Our Department of Mathematical Sciences embraces pure mathematics, applied mathematics and statistics, and operational research, and our course offers you the opportunity to study statistics alongside other mathematical subjects.

Providing a balance of solid statistical theory and practical application, this course builds your knowledge in all areas of statistics, data analysis and probability. You also have the opportunity to specialise, taking optional modules in topics including:
-Survey methodology
-Operations research
-Applied mathematics
-Computer science

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

Our expert staff

Our Department of Mathematical Sciences 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

Working in industries such as health, business, social care and finance, graduates are consistently in demand, working on projects such as efficacy of social policy, comparable data of cardiac rehabilitation and manipulation of raw data for academic research.

Our Masters graduates have progressed into careers in banking and finance, actuarial sciences, biological sciences, market research and statistics, management and consultancy etc.

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

-Modelling Experimental Data
-Statistical Methods
-Stochastic Processes
-Applied Statistics
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Nonlinear Programming (optional)
-Financial Modelling (optional)
-Research Methods in Finance: Empirical Methods in Finance (optional)
-Machine Learning and Data Mining (optional)
-Cloud Technologies and Systems (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Topics in Contemporary Social Theory (optional)
-Introduction to Survey Design and Management (optional)
-Applied Sampling (optional)

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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. Read more

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.

About this degree

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 healthcare 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.

Further information on modules and degree structure is available on the department website: Statistics (Medical Statistics) MSc

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.

Recent career destinations for this degree

  • Biostatistician, Boehringer Ingelheim
  • Statistical and Epidemiological Modeller, University of Oxford
  • PhD in Statistical Science, UCL
  • Graduate Bio-Statistician, PRA International

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, the pharmaceutical industry, NHS trusts and universities (e.g. London School of Hygiene & 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 UCL 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.



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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. Read more
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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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. Read more

Overview

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

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

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

This course is accredited by the Royal Statistical Society

Key facts:

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

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

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

- This course is accredited by the Royal Statistical Society.

Modules

Advanced Stochastic Processes

Applications of Statistics

Computational Statistics

Fundamentals of Statistics

Medical Statistics

Statistics Dissertation

Time Series and Forecasting

Topics in Biomedical Statistics

English language requirements for international students

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

Further information



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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. Read more

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 60 full-time academic staff.

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

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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The Oxford Master's in Mathematical Sciences (OMMS), provides a broad and flexible training in mathematical sciences, essential for research and innovation in the 21st century. Read more

The Oxford Master's in Mathematical Sciences (OMMS), provides a broad and flexible training in mathematical sciences, essential for research and innovation in the 21st century.

This MSc is run jointly by the Mathematical Institute and the Department of Statistics. It spans interdisciplinary applications of mathematics as well as recognizing fundamental questions and themes. Oxford has a world-class reputation in the mathematical sciences, and this master's degree offers students the opportunity to work with an international group of peers, including other mathematical leaders of the future.

This course draws on subjects in mathematics, statistics and computer science: from number theory, geometry and algebra to genetics and cryptography; from probability and mathematical geoscience to data mining and machine learning. You have the opportunity to choose from many different pathways, tailoring the programme to your individual interests and requirements. Examples of pathways include:

  • research in fundamental mathematics
  • data science
  • interdisciplinary research in fluid and solid mechanics
  • mathematical biology
  • industrially focused mathematical modelling
  • (stochastic) partial differential equations.

You will attend at least six units worth of courses (with one unit corresponding to a 16-hour lecture course supported by classes) in addition to writing a dissertation (worth two units). You will be encouraged to work collaboratively in classes, to develop your understanding of the material. Those wishing to extend themselves further might take one or two additional courses. 

The master's offers a substantial opportunity for independent study and research in the form of a dissertation. The dissertation is undertaken under the guidance of a supervisor and will typically involve investigating and writing in a particular area of mathematical sciences, without the requirement (while not excluding the possibility) of obtaining original results. A dissertation gives students the opportunity to develop broader transferable skills in the processes of organizing, communicating, and presenting their work, and will equip students well for further research or for a wide variety of other careers.

The Mathematical Institute is proud to have received an Athena SWAN silver award in 2017, reflecting its commitment to promoting diversity and to creating a working environment in which students and staff alike can achieve their full potential. The Department of Statistics is currently applying for a silver award. The departments offer extensive support to students, from regular skills training and career development sessions to a variety of social events in a welcoming and inclusive atmosphere.

This course runs from the beginning of October through to the end of June. Performance on the master's degree is assessed by invigilated written examinations and mini projects, and by the dissertation.



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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. Read more

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. The quantitative skills training provided by this MSc can lead to new and exciting opportunities in industry, medicine, government, commerce or research.

About this degree

The programme takes 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.

Further information on modules and degree structure is available on the department website: Statistics MSc

Careers

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

Recent career destinations for this degree

  • Data Analyst, Bupa
  • Quantitative Risk Analyst, Santander
  • PhD in Statistics, UCL
  • Management Associate, HSBC
  • Statistical Analyst, Nielsen

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.



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Postgraduate degree course in Mathematics, Operational Research, Statistics and Econometrics (MORSE) Masters/MSc. This programme is both technical and pragmatic. Read more

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

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

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

Course details

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

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

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

Related links 

Learning and teaching

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

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

Employability

Career opportunities

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

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

University Careers Network

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

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

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



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This course, commonly referred to as Part III, is a one-year taught Master's course in mathematics. Read more
This course, commonly referred to as Part III, is a one-year taught Master's course in mathematics. It is an excellent preparation for mathematical research and it is also a valuable course in mathematics and in its applications for those who want further training before taking posts in industry, teaching, or research establishments.

Students admitted from outside Cambridge to Part III study towards the Master of Advanced Study (MASt). Students continuing from the Cambridge Tripos for a fourth year, study towards the Master of Mathematics (MMath). The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree.

There are over 200 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. There are normally about 80 courses, covering an extensive range of pure mathematics, probability, statistics and the mathematics of operational research, applied mathematics and theoretical physics. They are designed to cover those advanced parts of the subjects that are not normally covered in a first degree course, but which are an indispensable preliminary to independent study and research. Students have a wide choice of the combination of courses that they offer, though naturally they tend to select groups of cognate courses. Normally classes are provided as back-up to lecture courses.

Visit the website: http://www.graduate.study.cam.ac.uk/courses/directory/mapmasmst

Course detail

The structure of Part III is such that students prepare between six and nine lecture courses for examination. These lecture courses may be selected from the wide range offered by both Mathematics Departments. As an alternative to one lecture course, an essay may be submitted. Examinations usually begin in late May, and are scheduled in morning and afternoon sessions, over a period of about two weeks. Two or three hours are allocated per paper, depending on the subject. Details of the courses for the current academic year are available on the Faculty of Mathematics website. Details for subsequent years are expected to be broadly similar, although not identical.

Most courses in the Part III are self-contained. Students may freely mix courses offered by the two Mathematics Departments. Courses are worth either two or three credit units depending on whether they last for 16 or 24 lectures respectively. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units. An essay (should a candidate choose to submit one) counts for 3 credit units. Part III is graded Distinction, Merit, Pass or Fail. A Merit or above is the equivalent of a First Class in other Parts of the Mathematical Tripos.

Learning Outcomes

After completing Part III, students will be expected to have:

- Studied advanced material in the mathematical sciences to a level not normally covered in a first degree;
- Further developed the capacity for independent study of mathematics and problem solving at a higher level;
- Undertaken (in most cases) an extended essay normally chosen from a list covering a wide range of topics.

Students are also expected to have acquired general transferable skills relevant to mathematics as outlined in the Faculty
Transferable Skills Statement http://www.maths.cam.ac.uk/undergrad/course/transferable_skills.pdf .

Format

Courses are delivered predominantly by either 16 or 24 hours of formal lectures, supported by additional examples classes. As an alternative to one lecture course, an essay may be submitted. There is also the possibiltiy of taking a reading course for examination. There are normally additional non-examinable courses taught each year.

Twice a year students have an individual meeting with a member of academic staff to discuss their progress in Part III. Students offering an essay as part of their degree may meet their essay supervisor up to three times during the academic year.

Assessment

Candidates may substitute an essay for one lecture course. The essay counts for 3 credit units.

Lecture courses are assessed by formal examination. Courses are worth either two or three credit units depending on whether they are 16 or 24 hours in length respectively. A 16 hour course is assessed by a 2 hour examination and a 24 hour course, a 3 hour examination. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units.

Continuing

MASt students wishing to apply for the PhD must apply via the Graduate Admissions Office for readmission by the relevant deadline. Applicants will be considered on a case by case basis and offer of a place will usually include an academic condition on their Part III result.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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The Probability and Statistics group (4 Professors, 3 Senior Lecturers and 10 Lecturers) in the School of Mathematics have a long-standing reputation… Read more

The Probability and Statistics group (4 Professors, 3 Senior Lecturers and 10 Lecturers) in the School of Mathematics have a long-standing reputation and experience of offering one year, high quality taught courses in areas of Statistics leading to the degree of MSc.These courses have aimed to offer a thorough professional training which prepare students to embark on statistical careers in a variety of areas. (There is a shortage of statisticians trained to postgraduate level in the UK and the employment prospects for such people remain good.)   They have also provided a very good foundation for further study at PhD level.

Our current MSc programme in Statistics allows students to take one of two different MSc degrees, depending on their interests and career aspirations. There is the main programme in Statistics and one associated pathway in Financial Statistics. Each is built around a common core of five modules and then students study an additional set of three specialist modules to make a total of eight in all. 

Coursework and assessment

There are two teaching semesters of 12 weeks each and approximately 15 weeks of project work. Assessment for the taught part is by exams and coursework. Following the successful completion of the taught part of the programme (worth a total of 120 credits) students are then expected to work on a dissertation from June to September which is worth a further 60 credits, making 180 credits in total. Information on the various topics and projects which will be available for dissertation are provided to the students in May from which they are invited to state their preferences.  

Course unit details

The taught part of the programme is divided into two 12-week semesters, each followed by a two-week period of examinations. This in turn is followed by a period of approximately 12 weeks of research work over the summer which is supervised by a member of the academic staff and ends with submission of the MSc dissertation in September. In the taught part of the course, full-time students attend weekly lectures and support classes for four modules (4 x 15 credits) in each semester. Students are also able to enrol on a part-time basis if they wish. In this case they study over a two year period and only take two modules per semester, with the dissertation being completed at the end of the second year. Details of the programme structure are given below.

Main MSc Statistics

  Semester One:

  • Linear Models & Nonparametric Regression
  • Statistical Computing
  • Statistical Inference
  • Multivariate Statistics

 Semester Two:

  • Generalized Linear Models & Survival Analysis
  • Longitudinal Data Analysis
  • Markov Chain Monte Carlo (MCMC)
  • Design and Analysis of Experiments

 This degree is accredited by the Royal Statistical Society.

Financial Statistics Pathway

This comprises a core of five modules which are common to the main programme, plus three specialist modules in financial statistics.

Semester One:

  • Linear Models & Nonparametric Regression
  • Statistical Computing
  • Statistical Modelling in Finance
  • Extreme Values and Financial Risk

 Semester Two:

  • Generalized Linear Models & Survival Analysis
  • Longitudinal Data Analysis
  • Markov Chain Monte Carlo (MCMC)
  • Time Series Analysis and Financial Forecasting

This degree is also accredited by the Royal Statistical Society.

Accreditation by the Royal Statistical Society (RSS) provides reassurance that our MSc programme produces graduates with the technical skills and subject knowledge required of a statistician. This provides our graduates with a competitive edge in the job market and provides employers with an assurance of quality of our degree.

Dissertation  Following the successful completion of the taught part of the programme (worth a total of 120 credits) students are then expected to work on a dissertation from June to September which is worth a further 60 credits, making 180 credits in total. Information on the various topics and projects which will be available for dissertation are provided to the students in May from which they are invited to state their preferences.  

Facilities

The School of Mathematics is the largest in the UK with an outstanding research reputation andfacilities .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

These programmes will prepare students for a broad range of statistical careers, particularly in the financial, medical, pharmaceutical and industrial sectors of the economy, but also with local and national government agencies, as well as in other areas. They will also provide an excellent foundation for students wishing to pursue advanced postgraduate research in statistics.



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The Higher Diploma in Statistics course is designed for graduates whose degrees have substantial mathematical content, and who want to develop their expertise in the application of statistical methods and broaden their career opportunities. Read more
The Higher Diploma in Statistics course is designed for graduates whose degrees have substantial mathematical content, and who want to develop their expertise in the application of statistical methods and broaden their career opportunities. The course may also be taken as a foundation for entry into the MSc Degree in Statistics. The course may be taken over one year (full time) or two years (part time).

There is a continuing demand by employers for numerate graduates. There are many new opportunities in commerce, government, industry, medicine and research for graduates who have added to their first degree with the training in quantitative and computing skills provided by the Higher Diploma in Statistics.

Visit the website: http://www.ucc.ie/en/cko07/

Course Details

This course provides you with a thorough theoretical grounding in statistics as well as a giving you practical experience of analysing real data.

Format

The Higher Diploma in Statistics consists of coursework divided into nine core modules. These modules are a blend of theoretical and applied statistics.

Students attend an average of 12 lectures, three tutorials and three computer practicals per week over the 24-week academic year. All modules have elements of continuous assessment which you submit throughout the course.

Lectures, tutorials and computer practicals take place between 9am and 6pm, Monday to Friday/

Modules (60 credits)

Probability and Mathematical Statistics (10 credits)
Statistical Theory (10 credits)
Introduction to Regression Analysis (5 credits)
Data Analysis I (5 credits)
Generalised Linear Models (5 credits)
Time Series (5 credits)
Survival Analysis (5 credits)
Current Topics in Statistics I (5 credits)
Statistical Consulting (10 credits)

The applied modules also equip you with advanced practical software-oriented skills in popular statistical software packages such as R, SAS andSPSS.

Students taking the part-time option take 25 credits in year 1 and the remaining 35 credits in year 2.

Assessment

Five modules (30 credits) are examined exclusively by continuous assessment. The remaining four modules (30 credits) are examined by both continuous assessment (worth 20% of the module mark) and end-of-year written examinations (worth 80% of the module mark).

The continuous assessments can be written home-work, computer practical assignments, in-class tests, written data analysis reports or computer practical examinations.

Careers

The course offers you the opportunity for further study at master’s degree level or employment in areas such as medical research, the pharmaceutical industry, government departments/agencies, sales and marketing research, finance and banking, the insurance industry and software development and support.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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This programme introduces you to the methods of statistical analysis, together with the underlying theory and some of the associated mathematics. Read more
This programme introduces you to the methods of statistical analysis, together with the underlying theory and some of the associated mathematics. The graduate diploma gives you the chance to study one or more specific areas of statistics in greater depth.

You will gain an understanding of statistical methods and will be able to apply them to the analysis of real-world data sets. You will also learn how to use statistical computer packages.

Visit the website http://www.bbk.ac.uk/study/2016/postgraduate/programmes/GDGSTATI_C/

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 (http://www.bbk.ac.uk/news/ref-results/), which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

Read about Birkbeck research offering insights and expertise to inform business, contribute to economic success and develop ground-breaking technologies (http://www.bbk.ac.uk/business/our-research).

Why study this course at Birkbeck?

- Provides an introduction to the main methods of statistical analysis used in business and scientific research.

- Ideal as a way to top up existing knowledge, as preparation for further graduate study or as a stand-alone course.

- Watch videos of our postgraduate students discussing their experience of studying at Birkbeck (http://www.bbk.ac.uk/mybirkbeck/get-ahead-stay-ahead/student-experience-videos).

Course structure

You take 2 compulsory year-long modules, which form the Graduate Certificate in Statistics, designed to give you a thorough grounding in mathematical and statistical methods as a basis for the postgraduate study of statistics.

Then you take 2 further modules, including at least 1 module from: Statistical Modelling; or Probability Models and Time Series.

Compulsory modules:
Advanced Mathematical Methods
Statistics: Theory and Practice

Option modules:
Probability Models and Time Series
Statistical Modelling

Teaching and assessment

Teaching
Mainly by lectures, but you will take part in practical sessions using a statistical package as part of the Statistics: Theory and Practice module.

Assessment
Coursework makes up 20% of the assessment of all modules. The rest of the assessment is by examinations taken in the summer term.

Careers and employability

Graduates can pursue careers in data collection, research, and analysis, modelling and forecasting. Possible professions include statistician, operational researcher, or research scientist (maths). This degree may also be useful in becoming a forensic statistician or high education lecturer.

Find out more about these professions (http://www.prospects.ac.uk/options_with_your_subject.htm).

Find out more about the destinations of graduates in this subject (http://www.bbk.ac.uk/prospective/careers-and-employability/department-of-economics-mathematics-and-statistics).

We offer a comprehensive Careers and Employability Service to help you advance your career, while our in-house, professional recruitment consultancy, Birkbeck Talent, works with London’s top employers to help you gain work experience that fits in with your evening studies.

Find out how to apply here - http://www.bbk.ac.uk/prospective/postgraduate/apply

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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. Read more
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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