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Mathematics×

Masters Degrees in Statistics

We have 111 Masters Degrees in 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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Looking for high-quality training in statistics for research or for professional life? If so, consider KU Leuven's MSc in Statistics, an interdisciplinary programme whose teaching is grounded in internationally-recognised research. Read more

Looking for high-quality training in statistics for research or for professional life? If so, consider KU Leuven's MSc in Statistics, an interdisciplinary programme whose teaching is grounded in internationally-recognised research. Choose from a number of approaches: biometrics, social behavioural and educational statistics, business statistics, industrial statistics, general statistical methodology, or an all-round statistics profile.

What is the Master of Statistics all about?

This master’s programme is offered by the Leuven Statistics Research Centre (LStat) of KU Leuven. It is accredited by the Royal Statistical Society. You’ll be trained intensively in both the theoretical and practical aspects of statistics. The programme will also help you develop a problem-solving attitude and teach you how to apply statistical methodology.

This is an initial Master's programme and can be followed on a full-time or part-time basis.

Structure

The 120-ECTS programme consists of a common core curriculum (one semester), option-specific courses (one semester), elective courses (one semester), and a master’s thesis.

  • Common core curriculum (30 ECTS): these course are compulsory for every student.
  • Option-specific courses (min. 32 ECTS). Within your selected option, you choose courses worth a total of minimum 32 ECTS.
  • Elective courses (30 ECTS)

To tailor the programme to your needs and interests, you choose one of the following options:

  • Biometrics;
  • Social, Behavioural, and Educational Statistics;
  • Business Statistics;
  • Industrial Statistics;
  • General Statistical Methodology;
  • Official Statistics;
  • All-round Statistics.

Department

LStat hosts international experts and is a stimulating environment for multidisciplinary statistical research. LStat is a privileged meeting space for statistics researchers from a range of domains:

  • Biostatistics;
  • Social, Behavioural and Educational Statistics;
  • Business and Industrial Statistics;
  • Statistical Methodology.

Objectives

The master of Statistics:

KNOWLEDGE AND INSIGHT

  • possesses thorough knowledge of and insight in the field of Statistics
  • has a perspective on the research and consulting aspects of one or more statistical fields within at least one of the following: biometry, industrial statistics, social behavioral and educational statistics, business statistics, statistical methodology, official statistics.
  • understands similarities and differences between different statistical methodology and practice across different sub-fields of statistics.

APPLYING KNOWLEDGE AND INSIGHT

  • has the competences and the insight to take the following steps in their own scientific research within a research team
  • can handle scientific quantitative research questions in the application area, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software.
  • has the skills and the habit to assess data quality and integrity.
  • is aware of the ethical, moral, legal, policy making, and privacy context of statistics and shows conduct accordingly.

DEVELOPING AN OPINION

  • appreciates the international nature of the field of statistical science.
  • is aware of the societal relevance of statistics.
  • can critically appraise methodology and challenge proposals for reported results of data analysis.

COMMUNICATION

  • can work in an intercultural, and international team, and understands the need and importance of working in a multidisciplinary team.
  • is an effective written and oral communicator, as well as an effective negotiator, both within their own field as well as towards other disciplines in the context of multidisciplinary projects.
  • is aware of the common stakeholders and the need for assertive and empathic interaction with them.

LEARNING SKILLS

  • is capable of acquiring new knowledge.

DEPENDING ON THE CHOSEN OPTION, THE STUDENT MASTERS FOLLOWING ADDITIONAL LEARNING OUTCOMES:

  • the master can act as a statistical consultant to subject-matter scientists and practitioners or/and as a collaborative researcher in an area of specialisation.

Career perspectives

As statistician, you'll be recruited by industry, banks or government institutions. You may find yourself designing clinical trials and supporting the biomedical sector, coaching research for new medicines, setting up and analysing psychological tests and surveys, performing financial risk analyses, statistically managing R&D projects and quality controls, or developing statistical software. And don't forget the academic world. The applications of statistics are very diverse, just like your professional options. 



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About the MSc programme. The MSc Statistics (Social Statistics) aims to provide high-level training in the theory and application of modern statistical methods, with a focus on methods commonly used in the social sciences. Read more

About the MSc programme

The MSc Statistics (Social Statistics) aims to provide high-level training in the theory and application of modern statistical methods, with a focus on methods commonly used in the social sciences.

You will gain insights into the design and analysis of social science studies, including large and complex datasets, study the latest developments in statistics, and learn how to apply advanced methods to investigate social science questions.  

The programme includes two core courses which provide training in fundamental aspects of probability and statistical theory and methods, the theory and application of generalised linear models, and programming and data analysis using the R and Stata packages. These courses together provide the foundations for the optional courses on more advanced statistical modelling, computational methods and statistical computing. Options also include specialist courses from the Departments of Methodology, Economics, Geography and Social Policy. 

Research Stream

The Research stream is similar to the nine-month programme, but will include a dissertation component, extending the programme to twelve months.

Graduate destinations

There is a high demand for graduates with advanced statistics training and an interest in social science applications, and students on this programme have excellent career prospects. 

Potential employers include the public sector (the Office for National Statistics, government departments, universities), market research organisations, survey research organisations and NGOs. This programme would be ideal preparation for doctoral research in social statistics or quantitative social science.

Further information on graduate destinations for this programme



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About the MSc programme. The Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance. Read more

About the MSc programme

The Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance.

It provides high-level training in statistics with applications in finance and econometrics. You will learn to analyse and critically interpret data, build statistical models of real situations, and use statistical software packages. 

The compulsory courses consolidate your understanding of fundamental ideas in probability and statistics and introduce advanced topics. You can choose options to focus on statistics with applications in social science or in finance and econometrics. 

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society if a specific combination of modules is taken. 

Research Stream

The research stream is similar to the nine-month programme but involves a compulsory dissertation which replaces one unit's worth of optional courses and extends the length of the programme to 12 months.

Graduate destinations

The programme provides excellent opportunities for employment and further study. The programme is also conditionally accredited by the Royal Statistical Society. This means that although an accreditation is given, it will only lead to the award of ‘Graduate Statistician’ if you take a specific combination of modules.

Further information on graduate destinations for this programme



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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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This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics. Read more
This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.

Why this programme

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

Programme structure

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

Core courses (compulsory)
◾Bayesian statistics
◾Generalised linear models
◾Introduction to R programming
◾Probability 1
◾Regression models
◾Statistical inference 1
◾Statistics project and dissertation.

Optional courses (six chosen, but at least one course must be from Group 1)

Group 1
◾Data analysis
◾Professional skills.

Group 2
◾Biostatistics
◾Computational inference
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Financial statistics
◾Functional data analysis
◾Machine learning
◾Multivariate methods
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾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) - assessed by a dissertation.

Career prospects

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

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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.

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

Why this programme

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

Programme structure

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

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

Career prospects

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

Graduates of this programme have gone on to positions such as:
Research Officer Medical Statistics at Kenya Medical Research Institute (KEMRI) Welcome Trust.

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This programme qualifies for the prestigious Data Lab Masters Scholarships. The award covers full tuition fee costs. For further information please see. Read more
This programme qualifies for the prestigious Data Lab Masters Scholarships. The award covers full tuition fee costs. For further information please see: Data Lab Masters Scholarships.

Why this programme

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

Programme structure

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

Courses include (twelve chosen)
◾Advanced Bayesian methods
◾Advanced data analysis
◾Bayesian statistics
◾Biostatistics
◾Computational inference
◾Data analysis
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Flexible regression
◾Financial statistics
◾Functional data analysis
◾Generalised linear models
◾Introduction to R programming
◾Linear mixed models
◾Machine learning
◾Multivariate methods
◾Principles of probability and statistics
◾Professional skills
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾Time series
◾Statistics project and dissertation.

Summer (May – August)
Statistics project and dissertation (60) - 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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About the MSc programme. The MSc Statistics provides intensive training in statistics applicable to the social sciences, economics and finance. Read more

About the MSc programme

The MSc Statistics provides intensive training in statistics applicable to the social sciences, economics and finance.

The aim of the programme is to foster an interest in theoretical and applied statistics and equip you for work as a professional statistician. You will learn to analyse and critically interpret data, build statistical models of real situations, and use programming tools and statistical software packages. 

The compulsory course will provide you with comprehensive coverage of fundamental aspects of probability and statistical methods and principles. It provides the foundations for the optional courses on more advanced statistical modelling, computational methods, statistical computing and advanced probability theory. Options also include specialist courses from the Departments of Methodology, Management, Mathematics, Economics and Social Policy. 

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society. 

MSc Statistics (Research)

The research stream is similar to the MSc Statistics nine-month programme but involves a compulsory dissertation which replaces one unit's worth of optional courses and extends the length of the programme to 12 months. 

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society.

Graduate destinations

Students on this programme have excellent career prospects. Former students have taken up positions in consulting firms, banks and in the public sector. Many go on to take higher degrees. Graduates of the MSc are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society.

Further information on graduate destinations for this programme



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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 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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This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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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. 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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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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Statistics is the study of the collection, analysis, interpretation, presentation and organisation of data. Read more

About the course

Statistics is the study of the collection, analysis, interpretation, presentation and organisation of data. Statistical analysis and data analytics is listed as one of the highly desirable skills employers are looking for, and with data becoming an ever increasing part of modern life, the talent to extract information and value from complex data is scarce.

The new Statistics and Data Analytics MSc is designed to train the next generation of statisticians with a focus on the field of data analytics. Employers expect skills in both statistics and computing. This master’s programme will provide a unique and coherent blend of modern statistical methods together with the associated computational skills that are essential for handling large quantities of unstructured data. This programme offers training in modern statistical methodology, computational statistics and data analysis from a wide variety of fields, including financial and health sectors.

Aims

Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. The aim of the MSc Statistics and Data Analytics is to produce graduates that:

- Are equipped with a range of advanced statistical methods and the associated computational skills for handling large quantities of unstructured data
- Have developed a critical awareness of the underlying needs of industry and commerce through relevant case studies
- Are able to analyse real-world data and to communicate the output of sophisticated statistical models in order to inform decision making processes
- Have the necessary computational skills to build and analyse simple/appropriate solutions using statistical Big Data technologies

Course Content

Compulsory modules:

Quantitative Data Analysis
Research Methods and Case Studies
Computer Intensive Statistical Methods
Modern Regression and Classification
Data Visualisation
Big Data Analytics
Time Series Modelling
Network Models
Dissertation

Statistics with Data Analytics Dissertation
Towards the end of the Spring Term, students will choose a topic for an individual research project, which will lead to the preparation and submission of an MSc dissertation. The project supervisor will usually be a member of the Brunel Statistics or Financial Mathematics group. In some cases the project may be overseen by an external supervisor based in industry or another academic institution..

Teaching

You’ll be taught using a range of teaching methods, including lectures, computer labs and discussion groups. Lectures are supplemented by computer labs and seminars/exercise classes and small group discussions. The seminars will be useful for you to carry out numerical data analysis, raise questions arising from the lectures, exercise sheets, or self-studies in an interactive environment.

The first term provides a thorough grounding in core programming, statistical and data analysis skills. In addition to acquiring relevant statistical and computational methods, students are encouraged to engage with real commercial and/or industrial problems through a series of inspiring case studies delivered by guest speakers. Support for academic and personal growth is provided through a range of workshops covering topics such as data protection, critical thinking, presentation skills and technical writing skills.

You’ll also complete an individual student project supervised by a relevant academic on your chosen topic.

Assessment

The assessment of all learning outcomes is achieved by a balance of coursework and examinations. Assessments range from written reports/essays, group work, presentations through to conceptual/statistical modelling and programming exercises, according to the demands of particular modular blocks. Additionally, class tests are used to assess a range of knowledge, including a range of specific technical subjects.

Special Features

The Statistics Group is a growing, highly-research active group, with collaborations across industry and academia, including engineering and pharmaceutical companies, Cambridge University and Imperial College London

Brunel’s Mathematics department is a member of the London Graduate School in Mathematical Finance. This consortium of mathematical finance groups comprises Birkbeck College, Brunel University London, Imperial College London, King’s College London, London School of Economics and Political Science and University College London. 

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